Article

Dexen: A scalable and extensible platform for experimenting with population-based design exploration algorithms

Authors:
To read the full-text of this research, you can request a copy directly from the author.

Abstract

A platform for experimenting with population-based design exploration algorithms is presented, called Dexen . The platform has been developed in order to address the needs of two distinct groups of users loosely labeled as researchers and designers . Whereas the researchers group focuses on creating and testing customized toolkits, the designers group focuses on applying these toolkits in the design process. A platform is required that is scalable and extensible: scalable to allow computationally demanding population-based exploration algorithms to be executed on distributed hardware within reasonable time frames, and extensible to allow researchers to easily implement their own customized toolkits consisting of specialized algorithms and user interfaces. In order to address these requirements, a three-tier client–server system architecture has been used that separates data storage, domain logic, and presentation. This separation allows customized toolkits to be created for Dexen without requiring any changes to the data or logic tiers. In the logic tier, Dexen uses a programming model in which tasks only communicate through data objects stored in a key-value database. The paper ends with a case study experiment that uses a multicriteria evolutionary algorithm toolkit to explore alternative configurations for the massing and façade design of a large residential development. The parametric models for developing and evaluating design variants are described in detail. A population of design variants are evolved, a number of which are selected for further analysis. The case study demonstrates how evolutionary exploration methods can be applied to a complex design scenario without requiring any scripting.

No full-text available

Request Full-text Paper PDF

To read the full-text of this research,
you can request a copy directly from the author.

... Over the past two decades, the authors have developed several design optimization systems aiming to tackle similar issues. Janssen (2013,2015) developed the Dexen system, tackling the slow computation times by parallelizing the execution in the cloud (Janssen, 2015). Wang et al. (2019) and Wang et al. (2020a) developed the EvoMass system, tackling the steep learning curve by creating generic procedures applicable to many design scenarios. ...
... Wortmann and Fischer (2020) have argued that for design optimization problems, multiobjective approaches come with many drawbacks. Our own experiences developing multiobjective optimization systems ( Janssen, 2015) have led us to similar conclusions. We found that search efficiency can be significantly reduced. ...
... The cloud computing platform used by the M€ obius Evolver allows searches generating thousands of designs to be completed in just a few minutes. This contrasts dramatically with many previous evolutionary design examples from the research, where evolutionary optimization can take many hours or even days to complete, even when using parallelization ( Janssen, 2015;Nguyen et al., 2014). ...
Chapter
During the early stages of design exploration, competing design strategies are typically considered. This chapter presents a design method, supported by a novel type of evolutionary algorithm, that maintains a heterogeneous population of design variants based on competing design strategies. Each strategy defines its own search space of design variants, all sharing a common generative concept or idea. A population of design variants is evolved through a process of selection and variation. As evolution progresses, some design strategies will become extinct while others will gradually dominate the population. A demonstration is presented showing how a designer can explore competing strategies by running a series of iterative evolutionary searches. The evolutionary algorithm has been implemented on a cloud platform, thereby allowing populations design variants to be processed in parallel. This results in a significant reduction in computation time, allowing thousands of designs to be evolved in just a few minutes.
... Somente mais recentemente estão sendo estruturados conhecimentos mais atrelados à prática da programação e computação, com os quais arquitetos esclarecem os pontos críticos das limitações de linguagens e paradigmas de programação (WOODBURY, 2010;JANSSEN;WEE, 2011;DAVIS, 2013;JANSSEN;STOUFFS, 2015). ...
... Somente mais recentemente estão sendo estruturados conhecimentos mais atrelados à prática da programação e computação, com os quais arquitetos esclarecem os pontos críticos das limitações de linguagens e paradigmas de programação (WOODBURY, 2010;JANSSEN;WEE, 2011;DAVIS, 2013;JANSSEN;STOUFFS, 2015). ...
... Os programas escritos em Dynamo não são portáveis para outros softwares BIM ou CAD e o trabalho dedicado pelo usuário na criação de um programa apenas funciona nesta VPL específica. Este é um caso de uma abordagem fortemente acoplada (JANSSEN, 2015). ...
Thesis
Full-text available
A pesquisa está inserida no contexto do Design Computacional, área que explora a computação como uma ferramenta de projeto de arquitetura. Para declarar e desenvolver projetos, é comum a utilização de linguagens de programação visual. No entanto, limitações no uso de linguagens visuais são reconhecidas, como as restrições encontradas na flexibilidade e escalabilidade dos códigos. Para estender o acesso à métodos de resolução de problemas nesses sistemas, usuários frequentemente recorrem ao uso de linguagens de programação textual, que permitem a utilização de mais estruturas de controle. Ainda assim, é comum que arquitetos sejam induzidos a realizar mudanças nos processos para acomodar a falta de controle e resultados inesperados de projeto. Isso acontece em parte pela falta de clareza em como utilizar a programação e todo o potencial dos métodos computacionais. Além disso, há uma falta de evidências empíricas usando projetos reais de arquitetura que apoiem discussões sobre o futuro das ferramentas de programação para arquitetos. Esta pesquisa investiga a comparação entre o uso de linguagens de programação visual e textual e visa sugerir diretrizes para melhorar as interfaces de programação utilizadas atualmente na área. Para isso, realizamos análises baseadas em métricas de avaliação de linguagens de programação e nas Dimensões Cognitivas (GREEN; PETRE, 1996). Adicionalmente, exploramos como estudo de aplicação um Projeto Orientado ao Desempenho, o Vancouver Academic Building do escritório americano Perkins+Will. O escritório implementou inicialmente o projeto usando a linguagem visual Grasshopper, com o objetivo de otimizar o design de uma fachada explorando o equilíbrio entre aspectos de iluminância e eficiência energética. Reimplementamos o estudo de aplicação utilizando uma linguagem textual e o ambiente de programação Rosetta (LOPES; LEITÃO, 2011). À medida que procuramos solucionar a lacuna existente na comparação dos fluxos de trabalho entre linguagens visuais e textuais recorrendo a um projeto real, selecionamos este estudo de aplicação porque ele abrange um processo orientado ao desempenho em vez de um projeto apenas paramétrico. Existem diferenças fundamentais encontradas entre estes dois fluxos de trabalho em relação a estratégias de escalabilidade e fluxo de dados, pois o orientado ao desempenho requer mais estruturas de controle como iteração e recursão. Identificamos diferenças relevantes entre ambas as linguagens e o potencial no uso das textuais no aumento significativo da escalabilidade do código e do modelo; aumento da confiabilidade dos resultados de desempenho do projeto e maior controle e clareza do processo utilizado. Apontamos também para as qualidades de interação e expressividade inerente das linguagens visuais. A partir do cruzamento teórico-prático, indicamos diretrizes que compõem em que medida o uso preferencial de linguagens textuais e linguagens híbridas (que integram ambas) podem melhorar a confiabilidade do Projeto Orientado ao Desempenho, assim como a possibilidade de aplicar métodos mais claros e eficazes no desenvolvimento do Projeto Algorítmico.
... For an architectural application of generative design, Shea et al. [13] introduced a performance-driven generative design method to lightweight cantilever roof structures while integrating two generative structural design systems, efiForm and Bentley's Generative Components. Other architectural generative design systems are ParaGen and Dexen for exploring parametric structures and façade designs were introduced by Turrin et al. [14] and Patrick [15]. Moreover, different researchers have also developed generative design techniques to create building [16] and site [17] layouts and energy efficient building designs [18]. ...
... After obtaining the dissimilarity ranks, the space-filling for the designs obtained from both techniques was calculated with Equation 15 by using the subjects' ranks as distances between the designs. In Equation 15, R pq denotes the dissimilarity rank between designs p and q given by the subject. Figure 10 (a), (b) and (c) shows the designs obtained, respectively, for the wine glass, wheel rim, and chair models using S-TLBO (which uses Euclidian distance metric for design exploration) and the proposed approach (in which designs are explored using psycho-physical distance metric). ...
... For the proposed approach, the design exploration process stopped at the 220 th , 150 th and 250 th iterations for the wine glass, wheel rim and chair models, respectively (see Figure 11). The plots in Figure 12 shows the space-filling values for the design alternatives in Figure 10, which were calculated with the dissimilarity ranks (R pq ) in Equation 15. In these plots, underlined numbers are the subjects who responded that S-TLBO generated better space-filling designs than proposed approach. ...
Article
Full-text available
In this paper, a generative design approach is proposed that involves the users' psychological aspect in the design space exploration stage to create distinct design alternatives. Users' perceptual judgment about designs is extracted as a psycho-physical distance metric, which is then integrated into the design exploration step to generate design alternatives for the parametric computer-aided design (CAD) shapes. To do this, a CAD model is first parametrized by defining geometric parameters and determining ranges of these parameters. Initial design alternatives for the CAD model are generated using Euclidean distance-based Sampling Teaching-Learning-Based Optimization (S-TLBO), which is recently proposed and can sample N space-filling design alternatives in the design space. Similar designs are then clustered and a user study is conducted to capture the subjects' perceptual response for the dissimilarities between the cluster pairs. Additionally, a furthest-point-sorting technique is introduced to equalize the number of designs in the clusters, which are being compared by the subjects in the user study. Afterward, nonlinear regression analyses are carried out to construct a mathematical correlation between the subjects' perceptual response and geometric parameters in the form of psycho-physical distance metric. Finally, a psycho-physical distance metric obtained is utilized to explore distinct design alternatives for the CAD model. Another user study is designed to compare the diversification between the designs when the Euclidean and suggested psycho-physical distance metrics are utilized. According to the user study, designs generated with the latter metric are more distinct.
... Caldas) [9][10] 和江山(P. Janssen) [11][12] ...
Article
Full-text available
对现有参数化建模和智能寻优算法技术在基于性能的设计优化方面的特点和局限性进行了剖析;根据设计师在方案阶段侧重于建筑设计探索和概念发生的工作特点,介绍了具有自主设计生成和探索能力的设计优化工具EvoMass,并展示了其在方案设计中的应用。应用结果表明,设计师可以通过EvoMass提取与建筑性能相关的设计信息,并将其融入概念发生和设计综合的过程之中。同时,EvoMass为性能设计优化流程提供了面向“人机协同的设计综合”的新方法范式。 This paper centers on the need for design exploration and concept development at the early-stage architectural design and investigates the limitations of current application of parametric modelling and computational optimization in performance-based design generation and exploration. In response to these limitations, the paper introduces an integrated design tool, called EvoMass, for building massing generation, optimization and exploration and demonstrates its utility in architectural design processes. The result shows that the designers can extract design information related to building performance from the optimization result and proactively use this information as a driving factor in the concept development and design synthesis processes. Finally, EvoMass facilitates a human-machine co-evolutionary design process in the early stages of architectural design.
... As each design generation and evaluation involve three independent simulations, most of the time for the optimization process is spent on simulation. In this regard, techniques such as cloud computing (Kyropoulou et al., 2018) and parallel computing (Janssen 2015) can be incorporated into the workflow to shorten the time for simulation. In addition, the recent advance in Machine Learning (ML) also provides a feasible approach to approximating or replacing the simulation. ...
Article
Full-text available
In performance-based architectural design optimization, the design of building massings and façades is commonly separated, which weakens the effectiveness in performance improvement. In response, this study proposes a hybrid massing-façade integrated design generation and optimization workflow to integrate the two elements in an evolutionary design process. Compared with the existing approaches, the proposed workflow emphasizes the diversity of building design generation, with which various combinations of building massing forms and façade patterns can be systematically explored. Two case studies and a corresponding comparison study are presented to demonstrate the efficacy of the proposed workflow. Results show that the optimization can produce designs coupling the potential of building massings and façades in performance improvement. In addition, the optimization can provide information that supports early-stage architectural design exploration. Such information also enables the architect to understand the performance implications associated with the synergy of building massing and façade design.
... The first assumption is outdated: There now is a consensus among computer scientists that Moore's Law is "dead", or at least slowing down, due to quantum-physical limits in the miniaturization of silicone chips (Eeckhout 2017). Parallel and cloud computing (Janssen 2015) provide at best partial solutions, since they result in diminishing returns: Parallel optimization steps (e.g. one generation of a genetic algorithm) allow only a wider, quasi-random search (i.e., exploration), but no deeper progress that benefits from previous steps (i.e., exploitation). ...
Conference Paper
Full-text available
This paper analyzes eight assumptions that underlie the general consensus in the computer-aided architectural design community that multi-objective optimization is more appropriate for and more analogous to architectural design processes than single-objective optimization. The paper discusses whether (a) architectural problems are best formulated as multi-objective optimization problems, (b) architectural design optimization is only about negotiating tradeoffs, (c) multiple objectives require multi-objective optimization, (d) Pareto fronts represent design spaces, (e) Pareto fronts require multi-objective optimization, (f) multi-objective algorithms are efficient and robust, (g) evolutionary operators make multi-objective algorithms efficient and robust and whether (h) computational cost is negligible. The paper presents practical examples of combining multiple objectives into one and concludes with recommendations for when to use single-and multi-objective optimization, respectively, and directions for future research.
... Despite many successful applications in the literature, applying performance-based optimization for building massing design exploration is still challenging. While certain barriers have been identified by other researchers, such as the lack of easy-to-use optimization tools and the problematic integration of optimization with architectural design [13][14][15], another critical barrier is the lack of topological variability among the variants offered by these techniques in the design space. ...
Article
Full-text available
For sustainable building design, performance-based optimization incorporating parametric modelling and evolutionary optimization can allow architects to leverage building massing design to improve energy performance. However, two key challenges make such applications of performance-based optimization difficult in practice. First, due to the parametric modelling approaches, the topological variability in the building massing variants is often very limited. This, in turn, limits the scope for the optimization process to discover high-performing solutions. Second, for architects, the process of creating parametric models capable of generating the necessary topological variability is complex and time-consuming, thereby significantly disrupting the design processes. To address these two challenges, this paper presents a parametric massing algorithm based on the subtractive form generation principle. The algorithm can generate diverse building massings with significant topological variability by removing different parts from a predefined volume (food4rhino.com/node/2974). Additionally, the algorithm can be applied to different building massing design scenarios without additional parametric modelling being required. Hence, using the algorithm can help architects achieve an explorative performance-based optimization for building massing design while streamlining the overall design process. Two case studies of daylighting performance optimizations are presented, which demonstrate that the algorithm can enhance the exploration of the potential in building massing design for energy performance improvements.
... Some researchers have also introduced some applicationspecific generative design systems, such as ParaGen, Dexen and GENE ARCH, which were introduced by Turrin et al. [46], Patrick [47] and Caldas [48] for exploring parametric structures, façade and energy efficient building designs, respectively. ...
Article
Full-text available
In the present work, a new digital design system, GenYacht, is proposed for the creation of optimal and user-centred yacht hull forms. GenYacht is a hybrid system involving generative and interactive design approaches, which enables users to create a variety of design alternatives. Among them, a user can select a hull design with desirable characteristics based on its appearance and hydrostatics/hydrodynamic performance. GenYacht first explores a given design space using a generative design technique (GDT), which creates uniformly distributed designs satisfying the given design constraints. These designs are then presented to a user and single or multiple designs are selected based on the user's requirements. Afterwards, based on the selections, the design space is refined using a novel space-shrinking technique (SST). In each interaction, SST shrinks the design space, which is then fed into GDT to create new designs in the shrank space for the next interaction. This shrinkage of design space guides the exploration process and focuses the computational efforts on user-preferred regions. The interactive and generative design steps are repeated until the user reaches a satisfactory design(s). The efficiency of GenYacht is demonstrated via experimental and user studies and its performance is compared with interactive genetic algorithms.
... In order to improve search efficiency, the steady-state replacement strategy may have certain advantages (Janssen, 2015). Compared with the generational replacement strategy, the steady-state replacement strategy evaluates only a small number of individuals and immediately replaces inferior individuals in the population. ...
Conference Paper
Full-text available
Standard evolutionary algorithms have limited use in practical architectural design tasks. This may be due to the poor search efficiency and the lack of diversity of the result. In order to overcome these weaknesses, this paper proposes a hybrid evolutionary algorithm combining an island model approach (parallel distributed technique) and a steady-state replacement strategy for maintaining a rich design diversity of the result while speeding up the search process. Through a demonstration, it is shown that the hybrid algorithm can effectively improve both design diversity and search efficiency.
Conference Paper
Full-text available
This paper presents a framework for rapid design optimization, which is aimed to support the iterative design optimization process. The framework consists of Rhino-Grasshopper and an evaluation server. In order to speed up the optimization process, three strategies are implemented in the framework, including parallel execution, early abortion, and multi-resolution simulations. To examine the efficacy of the developed framework, a case-study design optimization is conducted, and different combinations of the strategies are tested and compared. The case study investigates the impact of the adopted strategies on the optimization process in terms of search efficiency and effectiveness, and the result of the case study also demonstrates that optimization can be significantly improved by the use of the adopted strategies.
Article
Study design: Proof of concept. Objectives: Standard Functional Electrical Stimulation (FES) systems can enhance motor learning in people with tetraplegia and are widely delivered by self-adhesive electrodes. Their limitations are dexterity, specific knowledge to place the electrodes on muscles, need to fix electrodes when they lose the gel layer, and time. We designed a new FES system, using an existing protocol of drinking-like movements, to the upper limb of a person with tetraplegia C5 that fits in any anthropometry and can be easily produced. Furthermore, we tested the system to assess its effectiveness and users' perception during FES rehabilitation. Setting: São Carlos, SP, Brazil. Methods: A shell was designed with parametric design and fast-fabrication methods, and a stimulation unit and a smartphone application were developed. Questionnaires assessed the perceptions of a patient and a physiotherapist, about the usability of the new system in relation to standard FES. Kinematic data of drinking-like movements were collected from the patient wearing both systems and compared with data from an aged-matched control subject. Results: The results are a personalized shell and an intuitive FES system, overcoming the limitations of standard FES. The new system suggested better wrist-flexion control shown by the mean angles (-18.93°), then the other system (-59.35°), and compared with the control (-10.97°). Conclusions: Fast-fabrication with parametric design offers a promising alternative for personalizing FES systems, with potential for home use. Further studies are required including randomized clinical trials.
Article
Simulation-Based Multi-Objective Optimization (SBMOO) methods are being increasingly used in conceptual architectural design. They mostly focus on the solving, rather than the re-formulation, of a Multi-Objective Optimization (MOO) problem. However, Optimization Problem Re-Formulation (Re-OPF) is necessary for treating ill-defined conceptual architectural design as an iterative exploration process. The paper proposes an innovative SBMOO method which builds in a dynamic and interactive Re-OPF phase. This Re-OPF phase, as the main novelty of the proposed method, aims at achieving a realistic MOO model (i.e., a parametric geometry-simulation model which includes important objectives, constraints, and design variables). The proposed method is applied to the conceptual design of a top-daylighting system, focusing on divergent concept generation. The integration of software tools Grasshopper and modeFRONTIER is adopted to support this application. The main finding from this application is that the proposed method can help to achieve quantitatively better and qualitatively more diverse Pareto solutions.
Conference Paper
The comparison of various competing design concepts during conceptual architectural design is commonly needed for achieving a good final concept. For this, computational design exploration is a key approach. Unfortunately, most of existing research tends to skip this crucial process, and purely focuses on the late-stage design optimization based on a single concept that, they assume, has been good enough or accepted already. This paper focuses on information or knowledge extracted from a multi-objective design exploration for the formulation of a good geometrical building design concept. To better support the exploration process, a new integration plug-in is developed to integrate parametric modelling software and process integration and optimization software. Through a case study that investigates the daylight and energy performances of a large indoor space, this paper 1) tackles the importance of design exploration on the formulation of a good design concept; 2) presents and shows the usability of the new integration plug-in for supporting the exploration process.
Article
The aim of this paper is to investigate the challenges associated with the industrial implementation of generative design systems. Though many studies have been aimed at validating either the technical feasibility or the usefulness of generative design systems, there is, however, a lack of research on the practical implementation and adaptation in industry. To that end, this paper presents two case studies conducted while developing design systems for industrial uses. The first case study focuses on an engineering design application and the other on an industrial design application. In both cases, the focus is on detail-oriented performance-driven generative design systems based on currently available computer-assisted design tools. The development time and communications with the companies were analyzed to identify challenges in the two projects. Overall, the results show that the challenges are not related to whether the design tools are intended for artistic or technical problems, but rather in how to make the design process systematic. The challenges include aspects such as how to fully utilize the potential of generative design tools in a traditional product development process, how to enable designers not familiar with programming to provide design generation logic, and what should be automated and what is better left as a manual task. The paper suggests several strategies for dealing with the identified challenges.
Conference Paper
Full-text available
Parametric modelling is a term widely used to describe a range of modelling approaches. This paper proposes a taxonomy that distinguishes types of parametric modelling in the way they support iteration. A generalized parametric model is described and used as an analytical device to investigate how different parametric modelling methods provide for iteration over list structures.
Conference Paper
Full-text available
Coming soon...
Conference Paper
Full-text available
ntegration of analyses into early design phases poses several challenges. An experimental implementation of an analysis framework in conjunction with an optimization framework ties au-thoring and analysis tools together under one umbrella. As a prototype it served intensive use-testing in the context of the SmartGeometry 2012 workshop in Troy, NY. In this prototype the data flow uses a mix of proprietary and publicised file formats, exchanged through publicly accessible interfaces. The analysis framework brokers between the parametric authoring tool and the analysis tools. The optimization framework controls the processes between the authoring tool and parametric engine on one side and the optimization algorithm on the other. In addition to some user-implemented analyses inside the parametric design model the prototype makes energy analysis and structural analysis available. The prototype allows testing assumptions about work flow, implementation, usability and general feasibility of the pursued approach.
Conference Paper
Full-text available
Visual programming languages enable users to create computer programs by manipulating graphical elements rather than by entering text. The difference between textual languages and visual languages is that most textual languages use a procedural programming model, while most visual languages use a dataflow programming model. When visual programming is applied to design, it results in a new modelling approach that we refer to 'visual dataflow modelling' (VDM). Recently, VDM has becoming increasingly popular within the design community, as it can accelerate the iterative design process, thereby allowing larger numbers of design possibilities to be explored. Furthermore, it is now also becoming an important tool in performance-based design approaches, since it may potentially enable the closing of the loop between design development and design evaluation. A number of CAD systems now provide VDM interfaces, allowing designers to define form generating procedures without having to resort to scripting or programming. However, these environments have certain weaknesses that limit their usability. This paper will analyse these weaknesses by comparing and contrasting three VDM environments: McNeel Grasshopper, Bentley Generative Components, and Sidefx Houdini. The paper will focus on five key areas: * Conditional logic allow rules to be applied to geometric entities that control how they behave. Such rules will typically be defined as if-then-else conditions, where an action will be executed if a particular condition is true. A more advanced version of this is the while loop, where the action within the loop will be repeatedly executed while a certain condition remains true. * Local coordinate systems allow geometric entities to be manipulated relative to some convenient local point of reference. These systems may be either two-dimensional or three-dimensional, using either Cartesian, cylindrical, or spherical systems. Techniques for mapping geometric entities from one coordinate system to another also need to be considered. * Duplication includes three types: simple duplication, endogenous duplication, and exogenous duplication. Simple duplication consists of copying some geometric entity a certain number of times, producing identical copies of the original. Endogenous duplication consist of copying some geometric entity by applying a set of transformations that are defined as part of the duplication process. Lastly, exogenous duplication consists of copying some geometric entity by applying a set of transformations that are defined by some other external geometry. * Part-whole relationships allow geometric entities to be grouped in various ways, based on the fundamental set-theoretic concept that entities can be members of sets, and sets can be members of other sets. Ways of aggregating data into both hierarchical and non-hierarchical structures, and ways of filtering data based on these structures need to be considered. * Spatial queries include relationships between geometric entities such as touching, crossing, overlapping, or containing. More advanced spatial queries include various distance based queries and various sorting queries (e.g. sorting all entities based on position) and filtering queries (e.g. finding all entities with a certain distance from a point). For each of these five areas, a simple benchmarking test case has been developed. For example, for conditional logic, the test case consists of a simple room with a single window with a condition: the window should always be in the longest north-facing wall. If the room is rotated or its dimensions changed, then the window must re-evaluate itself and possibly change position to a different wall. For each benchmarking test-case, visual programs are implemented in each of the three VDM environments. The visual programs are then compared and contrasted, focusing on two areas. First, the type of constructs used in each of these environments are compared and contrasted. Second, the cognitive complexity of the visual programming task in each of these environments are compared and contrasted.
Conference Paper
Full-text available
Performance-based design approaches typically use iterative simulation as a way of exploring design variants. For such approaches, the speed of execution of the simulations is critical to enabling a fluid and interactive design process. This research proposes an iterative simulation design method where simulations are configured to run in two modes: in fast mode, simulations produce less accurate results but due to their speed can be applied successfully within an iterative refinement process; in slow mode, the simulations produce more accurate results that can be used to verify the performance improvements achieved using the iterative refinement process. A case study is presented where the proposed method is used to explore performance improvements related to levels of incident illuminance and incident irradiance on windows
Conference Paper
Full-text available
Evolutionary developmental design (Evo-Devo-Design) is a design method that combines complex developmental techniques with an evolutionary optimisation techniques. In order to use such methods, the problem specific developmental and evaluation procedures typically need to be define using some kind of textual programming language. This paper reports on an alternative approach, in which designers can use Visual Dataflow Modelling (VDM) instead of textual programming. This research described how Evo-Devo-Design problems can defined using the VDM approach, and how they can subsequently be run using a Distributed Execution Environment (called Dexen) on multiple computers in parallel. A case study is presented, where the Evo-Devo-Design method is used to evolve designs for a house, optimised for daylight, energy consumption, and privacy.
Conference Paper
Full-text available
This paper focuses on using evolutionary algorithms during conceptual stages of design process for multi-criteria optimisation of building envelopes. An experiment is carried out in optimising a panelled building envelope. The design scenario for the experiment is based on the scenario described in Shea et al. (2006) for the building envelope of the Media Centre Building in Paris. However, in their research, the optimisation process only allowed panel configuration to be optimised. In this paper, the task is to approach the optimisation of the envelope of the same building, assuming it to be in the early phases of the design process. The space of possible solutions is therefore assumed to be much wider, and as a result both external building form and internal layout of functional activities are allowed to vary. The performance intent of the experiment remains the same as that of Shea et al. (2006), which was to maximise daylight and minimise afternoon direct sun hours in the building at certain specific locations.
Conference Paper
Full-text available
A novel encoding technique is presented that allows constraints to be easily handled in an intuitive way. The proposed encoding technique structures the genotype-phenotype mapping process as a sequential chain of decision points, where each decision point consists of a choice between alternative options. In order to demonstrate the feasibility of the decision chain encoding technique, a case-study is presented for the evolutionary optimization of the architectural design for a large residential building.
Thesis
Full-text available
With the continued advancement of computational tools for building design, performance has gradually been allowed to claim a more prominent role as a driving force behind design decisions. However, there is currently only limited direct energy performance feedback available for designers early in the design process where such decision making has the highest potential impact on the overall design’s energy performance. Therefore, this research aims to propose a design process framework that can provide designers a “designing-in performance” environment, where design decisions can be influenced by energy performance feedback during the early stages of the design process. In response to the overall aim of this research, the first objective is to identify the most potentially suitable method through investigating current and past efforts. Extensive literature review revealed that time constraints and interoperability issues between tools and expert domain knowledge are the primary obstacles faced by designers in exploring design alternatives with consideration for energy performance. Moreover, evidence suggests that Multidisciplinary Design Optimization (MDO) methodology presents the most potential to overcome these obstacles. This determination stems from the aerospace and automobile industries successfully integrating multiple engineering domains through MDO to optimize and identify the best-fit design among various competing objectives during the design process. As a result, it is the position of this research that providing the designers with a designer-oriented MDO framework during the early stages of design will allow energy performance feedback to influence their design decision-making based on their design goals, thereby resulting in higher-performing designs. However, the applications of MDO to the building industry are still in infancy, especially in relation to bridging energy performance and design form exploration during the early stages of the design process. As the applicability of this approach during the design process is yet to be fully explored, this task is the second objective of this research. More specifically, the second research objective is to identify the proposed framework characteristics that would assist the designers during the early stage design process and enable a “designing-in performance” environment. Also included in the second objective is the validation of the proposed framework against the identified criteria. In order to achieve this objective, this research first synthesizes the pertinent research findings in order to isolate the criteria for “designing-in performance” and identify the gaps in the extant approaches, which hindered their applicability to the design process. Based on these results, the research presents the theoretical structure of the proposed early stage designer-centered MDO framework, entitled Evolutionary Energy Performance Feedback for Design (EEPFD), which incorporates conceptual energy analysis and design exploration of complex geometry through an automated evolutionary searching method. EEPFD is a semi-automated design exploration process, enabled by a customized genetic algorithm (GA)-based multi-objective optimization (MOO) approach, to provide energy performance feedback in assisting design decision-making. In order to realize EEPFD for the purpose of validation and evaluation against the previously identified criteria, a prototype tool, H.D.S. Beagle, is developed to host the customized GA-based MOO algorithm. In H.D.S. Beagle, energy use intensity (EUI) is selected as the energy objective function. Also included are spatial programming compliance (SPC) and a schematic net present value (NPV) calculation for consideration in performance tradeoff studies. A series of hypothetical cases are used to form the initial framework, as well as obtain and evaluate the technology affordance of H.D.S. Beagle. These hypothetical cases are also used as a means to assess whether EEPFD demonstrates the potential to meet the needs of early stage design, where rapid design exploration and accommodation of varying degrees of geometric complexity are needed. Based on these results, EEPFD can be considered as suitable for further exploration in early stage design applications. Finally, the hypothetical cases are used to reaffirm the need of incorporating energy performance feedback during the early stages of the design process. The last research objective is to evaluate the impact of the proposed framework and availability of energy performance feedback on the early stage design process. To achieve this objective, evaluation metrics are first established to provide the means and measurements by which to conduct process evaluation and comparative studies in both the design profession and pedagogical case-based experiments. In the design profession case-based experiment, EEPFD is applied to a design competition open to professional design firms. In this case study, the chosen design firm utilizes three approaches in pursuing higher performance design: (1) collaboration with mechanical electrical and plumbing (MEP) consultants; (2) in-house analysis through available analytical tools; and (3) EEPFD application. While this case revealed that the output of these three approaches is not directly comparable, it is observed that EEPFD provides exploration of a greater number of design alternatives and tradeoff studies compared to the two conventional processes. The pedagogical case-based experiments conducted as a part of this study are divided into three sets, based on the setting—a computational classroom, a design studio, and a computational workshop setting. These experiments utilize the established benchmark process to (1) compare the human decision process against the automated EEPFD; (2) observe the ability of students to translate their design intent into a parametric model; and (3) gauge the impact of the availability of energy performance feedback on the early stage design process. The results obtained in these experiments indicate that EEPFD is capable of generating a solution space with a higher Pareto designated solution rate than the students can achieve. Moreover, it eliminates up to 50% of the human error rate, as observed in the manual exploration process. It is also observed that students are able to use the EEPFD-provided feedback to identify a design alternative that is not only consistent with their design exploration intent, but also improves upon the energy performance of their initial design. However, in all these case-based experiments, designers—both students and design professionals—encountered difficulties in translating their design intent into a parametric model compatible with the use of EEPFD. While this is acknowledged, it is likely that increased familiarity with parametric modeling techniques would overcome these observed difficulties. The significant contribution of this research is the EEPFD—a designer-oriented MDO framework enabling the combination of complex geometric form exploration via energy performance feedback. This tool addresses the observed gaps in the currently available solutions, thereby enabling further exploration of MDO application to the early stage design. Subsequently, this research provides the means and measurements to explore and evaluate the application of EEPFD to the early stages of design, identifying potentially advantageous adjustments from previously implemented MDO frameworks and the early stage design process. Considering the nature of early stage design in the architectural field—which consists of subjective and objective design requirements, time constraints, uncertainty regarding design components, and the unique conditions of each design problem—a best practice is proposed in applying EEPFD to early stage design, which significantly differs from the more common MDO application method of seeking a mathematically-defined convergence “best fit” solution set. Finally, this research provides a “designing-in performance” environment in which designers can use available energy performance feedback to influence their design decisions during the early stages of the design process, where such decisions have the greatest impact on the overall design’s energy performance.
Article
Full-text available
Architecture, Engineering, and Construction (AEC) professionals typically generate and analyze very few design alternatives during the conceptual stage of a project. One primary cause is limitations in the processes and software tools used by the AEC industry. The aerospace industry has overcome similar limitations by using Process Integration and Design Optimization (PIDO) software to support Multidisciplinary Design Optimization (MDO), resulting in a significant reduction to design cycle time as well as improved product performance. This paper describes a test application of PIDO to an AEC case study: the MDO of a classroom building for structural and energy performance. We demonstrate how PIDO can enable orders of magnitude improvement in the number of design cycles typically achieved in practice, and assess PIDO's potential to improve AEC MDO processes and products.
Article
Full-text available
This paper describes ThermalOpt—a methodology for automated BIM-based multidisciplinary thermal simulation intended for use in multidisciplinary design optimization (MDO) environments. ThermalOpt mitigates several technical barriers to BIM-based multidisciplinary thermal simulation found in practice today while integrating and automating commercially available technologies into a workflow from a parametric BIM model (Digital Project) to an energy simulation engine (EnergyPlus) and a daylighting simulation engine (Radiance) using a middleware based on the open data model Industry Foundation Classes (IFC). Details are discussed including methods for: automatically converting architectural models into multiple consistent thermal analytical models; integration/coordination of analysis inputs and outputs between multiple thermal analyses; reducing simulation times; and generating consistent annual metrics for energy and daylighting performance. We explain how ThermalOpt can improve design process speed, accuracy, and consistency, and can enable designers to explore orders of magnitude larger design spaces using MDO environments to better understand the complex tradeoffs required to achieve zero energy buildings.
Article
Full-text available
Spatial structures often embody generative systems. Both analog (physical modeling) as well as computational methods have been uses to explore the range of design possibilities. Whereas many of the favored physical modeling techniques, such as soap films or catenary nets, inherently generate forms based on certain performative properties, many of the parametric form generating computational methods derive form based solely on geometry, detached from physical performance. ParaGen has been developed as a tool to explore parametric geometry based on aspects of performance. Within the cyclic structure of a genetic algorithm, it incorporates parametric geometry generation, simulation for performance evaluation, and the ability to sort and compare a wide range of solutions based on single or multiple objectives. The results can be visually compared by teams of designers across a graphic web interface which includes the potential for human interaction in parent selection and breeding of further designs. The result is a tool which allows the exploration of the generative design space based on performance as well as visual criteria.
Article
Full-text available
While the overall performance of buildings has been established to be heavily impacted by design decisions made during the early stages of the design process, design professionals are typically unable to explore design alternatives, or their impact on energy profiles, in a sufficient manner during this phase. The research presents a new design simulation methodology based on incorporating a prototype tool (H.D.S. Beagle) that combines parametric modeling with multi-objective optimization through an integrated platform for enabling rapid iteration and trade-off analysis across the domains of design, energy use intensity, and finance. The research evaluates how the proposed method impacts design simulation processes, by either enabling and/or disrupting the early stages of design decision making. This simulation technology is presented through two major experiment sets: (1) a series of hypothetical cases emulating the architecture, engineering, and construction (AEC) design modeling and simulation process using our integrated simulation framework and technology; and (2) a pedagogically based experiment used for establishing benchmarks. Through these experiment data sets, both quantitative and qualitative data are collected, including human designer and computational analysis speeds, quantity of generated design alternatives, and quality of resulting solution space as defined by the evaluation metric of this research. The affordances for incorporation of real world design complexity into our computational design prototype and simulation methodology are discussed through both the enabling and the disruptive impact on the early stages of the design process.
Article
Full-text available
"October 2004" Thesis (Ph.D.)--The Hong Kong Polytechnic University, 2005. Includes bibliographical references.
Article
Multidisciplinary design optimization (MDO) has been identified as a potential means for integrating design and energy performance domains but has not been fully explored for the specific demands of early stage architectural design. In response a design framework, titled Evolutionary Energy Performance Feedback for Design (EEPFD), is developed to support early stage design decision-making by providing rapid iteration with performance feedback through parameterization, automation, and multi-objective optimization. This paper details the development and initial validation of EEPFD through two identified needs of early stage design: 1) the ability to accommodate formal variety and varying degrees of geometric complexity; and 2) the ability to provide improved performance feedback for multiple objective functions. Through experimental cases the research presents effective application of EEPFD for architectural design.
Article
The performance-oriented design of large roof structures for semi-outdoor spaces is investigated with the aim to integrate performance evaluations in the early stages of the design process. In particular, daylight and thermal comfort are improved under large structures by exploring passive solar strategies that reduce the need for imported energy. The performance oriented, parametric design approach we developed is structured in two parts. One part uses parametric geometry to generate design alternatives, and the other part uses performance based exploration and evaluation of alternatives. We discuss how the performance based exploration is accomplished using a tool called ParaGen. The potential of the method is shown in a case study of the SolSt roof. The design process of SolSt is based on parametric variations of its curvature, the density of its modules and the geometry of its cladding, and is explored based on daylight and solar exposure of the covered space.
Chapter
The preconceptions that designers bring to the table when they are considering a particular design task are an unavoidable and necessary part of the design process. This paper first reviews the literature relating to the role of preconceptions in design, and then goes on to discuss computational tools that support the development and expression of such design preconceptions. As an example of such a tool, an outline is given of a generative evolutionary design system that allows designers to evolve families of designs that embody preconceived values and ideas.
Conference Paper
This paper presents a recursive, dimension-sweep algorithm for computing the hypervolume indicator of the quality of a set of n non-dominated points in d > 2 dimensions. It improves upon the existing HSO (Hypervolume by Slicing Objectives) algorithm by pruning the recursion tree to avoid repeated dominance checks and the recalculation of partial hypervolumes. Additionally, it incorporates a recent result for the three-dimensional special case. The proposed algorithm achieves O(n<sup>d−2</sup>log n) time and linear space complexity in the worst-case, but experimental results show that the pruning techniques used may reduce the time complexity exponent even further.
Article
As the field of design automation and generative design systems (GDS) evolve, more emphasis is placed on issues of design evaluation. This paper focus on the presentation of different applications of GENE_ARCH, an evolution-based GDS aimed at helping architects to achieve energy-efficient and sustainable architectural solutions. The system applies goal-oriented design, combining a genetic algorithm (GA) as the search engine, with the DOE2.1E building energy simulation software as the evaluation module. Design evaluation is based on energy spent for heating, cooling, ventilation and artificial lighting in the building, and on sustainability issues like greenhouse gas emissions associated with the embodied energy of construction materials. The GA can work either as a standard GA or as a Pareto GA, for multicriteria search and optimization. In order to provide a broad view of the capabilities of the software, different applications are discussed: (1) standard GA: testing and validating the software; (2) standard GA: incorporation of architecture design intentions, using a building by architect Alvaro Siza; (3) Pareto GA: choice of construction materials, considering cost, building energy use, and embodied energy; (4) Pareto GA: application to Siza’s building, considering thermal and lighting behavior separately; (5) standard GA: shape generation with single objective function; (6) Pareto GA: shape generation with multicriteria evaluation; (7) Pareto GA: application to an urban and housing context. Overall conclusions from the different applications are discussed, as well as current challenges and limitations, and directions for further work.
Article
The potential of Multidisciplinary Design Optimization (MDO) is not sufficiently exploited in current building design practice. I argue that this field of engineering requires a special setup of the optimization model that considers the uniqueness of buildings, and allows the designer to interact with the optimization in order to assess qualities of aesthetics, expression, and building function. For this reason, the approach applies a performance optimization based on resource consumption extended by preference criteria. Furthermore, building design-specific components serve for the decomposition and an interactive way of working. The component scheme follows the Industry Foundation Classes (IFC) as a common Building Information Model (BIM) standard in order to allow a seamless integration into an interactive CAD working process in the future. A representative case study dealing with a frame-based hall design serves to illustrate these considerations. An N-Square diagram or Design Structure Matrix (DSM) represents the system of components with the disciplinary dependencies and workflow of the analysis. The application of a Multiobjective Genetic Algorithm (MOGA) leads to demonstrable results.
Article
In the course of a research project designed to test various hypotheses about the design of public housing, it has been found necessary to study the design process of some architects who had been interviewed earlier. A plea is made for the use of subjective rather than scientific methods in the analysis of this type of material, and by extension for greater emphasis on subjective methods in design. Many descriptions of the design process have been based on an analysis-synthesis model which does not correspond to the design process as seen in practice. A new paradigm has been offered by Hillier, Musgrove and O'Sullivan, one of conjecture-analysis. This is supported by evidence from the present research findings, and an elaboration is suggested to give a model of the design process consisting of generator-conjecture-analysis. The new element is the primary generator, a broad initial objective or small set of objectives, self-imposed by the architect, a value judgement rather than the product of rationality. Case material is presented to support the idea of the primary generator and the generator-conjecture-analysis model.
Article
The use of distributed data structures in a logically-shared memory is a natural readily-understood approach to parallel programming. The principle argument against such an approach for portable software has always been that efficient implementations could not scale to massively-parallel, distributed memory machines. Now, however, there is growing evidence that it is possible to develop efficient and portable implementations of virtual shared memory models on scalable architectures. In this paper we discuss one particular example: Linda. After presenting an introduction to the Linda model, we focus on the expressiveness of the model, on techniques required to build efficient implementations, and on observed performance both on workstation networks and distributed-memory parallel machines. Finally, we conclude by briefly discussing the range of applications developed with Linda and Linda`s suitability for the sorts of heterogeneous, dynamically-changing computational environments that are of growing significance. 28 refs.
Conference Paper
. Since 1985 various evolutionary approaches to multiobjectiveoptimization have been developed, capable of searching for multiplesolutions concurrently in a single run. But the few comparative studies ofdifferent methods available to date are mostly qualitative and restrictedto two approaches. In this paper an extensive, quantitative comparisonis presented, applying four multiobjective evolutionary algorithms to anextended 0/1 knapsack problem.1 IntroductionMany real-world...
Book
Genetic algorithms are founded upon the principle of evolution, i.e., survival of the fittest. Hence evolution programming techniques, based on genetic algorithms, are applicable to many hard optimization problems, such as optimization of functions with linear and nonlinear constraints, the traveling salesman problem, and problems of scheduling, partitioning, and control. The importance of these techniques is still growing, since evolution programs are parallel in nature, and parallelism is one of the most promising directions in computer science. The book is self-contained and the only prerequisite is basic undergraduate mathematics. This third edition has been substantially revised and extended by three new chapters and by additional appendices containing working material to cover recent developments and a change in the perception of evolutionary computation.
Article
Design tools that aim not only to analyse and evaluate, but also to generate and explore alternative design proposals are now under development. An evolutionary paradigm is presented as a basis for creating such tools. First, the evolutionary paradigm is shown to be the only successful design system on which this new phase of design tool could be based. Secondly, any characterisation of design as a search problem is argued to be a serious misconception. Instead it is proposed that evolutionary design systems should be seen as generative processes that are able to evaluate their own output. Thirdly, a generic framework for generative evolutionary design systems is presented. Fourth, the generative process is introduced as key element within this generic framework. The role of the environment within this process is fundamental. Finally, the direction of future research within the evolutionary design paradigm is discussed with possible short and long term goals being presented.
Article
Design tools that aim not only to analyse and evaluate, but also to generate and explore alternative design proposals are now under development. An evolutionary paradigm is presented as a basis for creating such tools. First, the evolutionary paradigm is shown to be the only successful design system on which this new phase of design tool could be based. Secondly, any characterisation of design as a search problem is argued to be a serious misconception. Instead it is proposed that evolutionary design systems should be seen as generative processes that are able to evaluate their own output. Thirdly, a generic framework for generative evolutionary design systems is presented. Fourth, the generative process is introduced as a key element within this generic framework. The role of the environment within this process is fundamental. Finally, the direction of future research within the evolutionary design paradigm is discussed with possible short and long term goals being presented.
Article
This paper describes a comprehensive framework for generative evolutionary design. The key problem that is identified is generating alternative designs with an appropriate level of variability. Within the proposed framework, the design process is split into two phases: in the first phase, the design team develops and encodes the essential and identifiable character of the designs to be generated and evolved; in the second phase, the design team uses an evolutionary system to generate and evolve designs that embody this character. This approach allows design variability to be carefully controlled. In order to verify the feasibility of the proposed framework, a generative process capable of generating controlled variability is implemented and demonstrated.
Article
Linda consists of a few simple operators designed to support and simplify the construction of explicitly-parallel programs. Linda has been implemented on AT&T Bell Labs' S/Net multicomputer and, in a preliminary way, on an Ethernet-based MicroVAX network and an Intel iPSC hypercube. Although the implementations are new and need refinement, early experiences with them are presented to support the claim that Linda is a promising parallel programming tool. Parallel programming in Linda is conceptually the same order of task as conventional programming in a sequential language. Some related higher-level parallel languages that can be implemented on top of the Linda kernel are also discussed, particularly the symmetric languages such as Pascal, C, and Lisp.
Using evolutionary algorithm as a design tool for the multi-criteria optimization of catenary structures
  • X W Lee
A conceptual seeding technique for architectural design. Int. Conf. Application of Computers in Architectural Design and Urban Planning
  • J H Frazer
  • J Connor
An urban farm typology to mitigate desertification in Wuwei
  • H Zhong
Cloud-based design analysis and optimization framework
  • V Mueller
  • T Strobbe