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Integrated scheduling optimization of production and transportation for precast component with delivery time window
Abstract
Purpose
Production and transportation of precast components, as two continuous service stages of a precast plant, play an important role in meeting customer needs and controlling costs. However, there is still a lack of production and transportation scheduling methods that comprehensively consider delivery timeliness and transportation economy. This article aims to study the integrated scheduling optimization problem of in-plant flowshop production and off-plant transportation under the consideration of practical constraints of customer order delivery time window, and seek an optimal scheduling method that balances delivery timeliness and transportation economy.
Design/methodology/approach
In this study, an integrated scheduling optimization model of flowshop production and transportation for precast components with delivery time windows is established, which describes the relationship between production and transportation and handles transportation constraints under the premise of balancing delivery timeliness and transportation economy. Then a genetic algorithm is designed to solve this model. It realizes the integrated scheduling of production and transportation through double-layer chromosome coding. A program is designed to realize the solution process. Finally, the validity of the model is proved by the calculation of actual enterprise data.
Findings
The optimized scheduling scheme can not only meet the on-time delivery, but also improve the truck loading rate and reduce the total cost, composed of early cost in plant, delivery penalty cost and transportation cost. In the model validation, the optimal scheduling scheme uses one less truck than the traditional EDD scheme (saving 20% of the transportation cost), and the total cost can be saved by 17.22%.
Originality/value
This study clarifies the relationship between the production and transportation of precast components and establishes the integrated scheduling optimization model and its solution algorithm. Different from previous studies, the proposed optimization model can balance the timeliness and economy of production and transportation for precast components.
... Scientific scheduling management is an important means to ensure timely project progress and reduce risks. Therefore, the production scheduling problem of prefabricated components around the flow production line has been widely explored by scholars [18][19][20][21][22][23][24][25][26]. The research on production scheduling optimization of prefabricated components on the flow line is essential work in the development of prefabricated buildings, and it is also an important branch of workshop scheduling academic research in the field of construction engineering. ...
... At present, scholars have investigated the single-line precast production scheduling issue [9,[27][28][29][30] and the integrated scheduling issue of single-line precast production and transportation [25,26,31,32]. These studies have not addressed the cooperative scheduling issue of multiple production lines, whereas multiple lines exist in the real-world production environment [24]. ...
... Du et al. [32] incorporated value management and just-in-time principles in lean construction into the precast production process and conducted real-time scheduling of prefabricated component production and transportation according to resource occupation and sudden events. Dan and Liu [25] sought a method for integrated scheduling of prefabricated component production and transportation that balances on-time delivery and transportation economy while considering multiple transportation constraints. However, the above papers do not address the cooperative scheduling problem of multiple production lines. ...
With the increasing popularity of prefabricated buildings, more and more precast plants have been equipped with multiple production lines to increase productivity and meet the growing market demand. Sharing equipment, human, and transportation resources is a typical feature of integrated scheduling management for precast production and transportation on multiple production lines. In response to these characteristics, this article studies the integrated scheduling optimization of multi-line production and transportation for prefabricated components. With on-time delivery and lower costs as the goals, a scheduling optimization mathematical model is established for this scenario. This article adopts the genetic algorithm to design the solution algorithm for this model, and the effectiveness of the model and algorithm is verified through an example. The results show that compared with the traditional scheduling scheme, this method can prominently reduce costs while promoting on-time delivery. The model and method can help the precast plant with multiple production lines improve efficiency and reduce costs, as well as enhancing the practicability of the precast production and transportation scheduling scheme.
... Given the complex, heterogeneous nature of transportation and supply chain management (SCM) in various industries (Stüve et al., 2022), the use of algorithms has been receiving widespread attention. Transportation management, with the aid of algorithms, for the distribution of long-haul goods plays an important role in reducing costs and time, and increasing customer satisfaction (Tavakkolimoghaddam et al., 2022;Dan & Liu, 2023). Gupta et al., (2022) also submit that transportation algorithms are deployed to minimize total transportation cost and inventory cost by determining optimal routes. ...
... Due to the complex, heterogeneous nature of transportation and supply chain management (SCM) in various industries (Stüve et al., 2022), managers have sought for ways to create place utility for customers, and reduce transportation time and cost through the use of algorithms (Gupta et al., 2022;Tavakkolimoghaddam et al., 2022;Dan & Liu, 2023). Classical transportation algorithms include; (i) Northwest Corner method (ii) Minimum cost method, and (iii) Vogel's approximation method. ...
This study explored the level of awareness and use of transportation algorithms among Production, Operations and Logistics Managers in Rivers State, Nigeria. The study employed a survey-based quasi-experimental research design. Thirty manufacturing and logics enterprises in the Trans-Amadi Industrial Area of Rivers were surveyed using a structured questionnaire. Copies of the questionnaire were administered to 53 managers. A total of 41 valid responses were collected were used for data analysis. The research used means to gauge the degree of awareness and usage. According to the findings, very few managers have ever heard of transportation algorithms. Many managers are aware of transportation algorithms but have never used them. Furthermore, an average number of production and operations managers use transportation algorithms only occasionally, while the majority of them do not use transportation algorithms on a regular basis. This implies that while managers are cognizant of transportation algorithms, they are hesitant to use them. As a result, the research suggests that manufacturing, operations, and logistics companies raise consciousness about the benefits of transportation algorithms through education initiatives and the formation of communities of practise. Firms should also educate managers on the use of transportation algorithms and make it obligatory whenever they move products from origin to destination. This is, as to the best of the researcher’s knowledge, the first study on the degree of awareness and usage of Transportation Algorithms among Production, Operations, and Logistics Managers in Rivers State, Nigeria.
... Dan and Liu [14] constructed an integrated model for scheduling of production and transportation precast elements with delivery time windows. Their objective function minimizes all of the following: in-plant early cost, the total penalty cost of delivery, and transportation cost. ...
Offsite construction technologies are developed to reduce project cost and duration. To make the most of the potential offered by prefabrication the planner should consider the whole supply chain. A failure to coordinate the off-site production with on-site erection is a source of waste (waiting time of the construction crews or redundant handling activities on-site). Most of the research to date focused on optimizing operations of a prefabrication plant assuming a deterministic schedule of demand for its products. The purpose of this paper is to develop a mathematical model for integrated scheduling of offsite and on-site operations. Its solution is a schedule that minimizes the downtime of both the prefabrication plant and the on-site erection crews. In accordance with the Just-in-Time concept, the prefabrication schedule is set in a way to reduce the stocks of finished products, thus reducing the storage area and cost of funds tied up in inventory. The schedule’s robustness against the disturbance in the production and erection workflows is assumed to be assured allocating time buffers. The advantage of the proposed method is the ease of collecting the input: instead of detailed cost records, estimates of unit cost of lost time can be used.
The construction industry is undergoing a fundamental transformation with the introduction of advanced digital technologies such as digital twins (DT), artificial intelligence (AI) and optimization. These technologies increase operational efficiency, improve maintenance, and promote sustainability. DT enable real-time monitoring and optimization of projects, while AI analyzes large data sets for predictive maintenance and resource optimization. Optimization algorithms support efficient planning, scheduling and cost reduction. Despite the benefits, challenges such as cybersecurity and data management remain. This chapter explores the synergy between these technologies, their benefits and the challenges for successful implementation in construction and provides recommendations for future research.
Reasonable production scheduling plays a vital role in the production of precast component factories. However, previous static scheduling models no longer fit actual production. In particular, some factors will cause errors in the actual delivery time of the components, including the lack or redundancy of processes in the model, resource constraints required by the core processes, and differences in transportation schemes. Moreover, the optimization goal of simply pursuing the minimization of fines from order delivery underestimates companies’ emphases on reputation. Therefore, this study proposes an improved model for precast component production scheduling considering resource constraints. The number of production processes is adjusted to eight, and three resource constraints for mold, steel, and concrete are added. An enterprise decision-making coefficient is introduced into the optimization object function, and the constraints of the transportation scheme are improved. Finally, a real case study is conducted to verify the applicability of the model. Compared with previous models, the developed model fills the gap in considering production resource constraints and enterprise decisions in precast production, can better meet diverse production conditions and business needs of factories for scheduling, and help give full play to the advantages of prefabricated construction.
Purpose: For many types of buildings, prefabricated prefinished volumetric construction (PPVC) is increasingly becoming a preferred alternative construction approach. Empirical evidence of project performance has consistently demonstrated that the ultimate success of PPVC projects is directly linked to the key decisions made at the outset of the PPVC project life cycle. However, there is limited knowledge of how to successfully manage these early stages. This research identified and evaluated the critical success factors (CSFs) required for the management of the conception, planning, and design stages of the PPVC project life cycle.
Design/Methodology/Approach: A multistage methodological framework was adopted to identify and evaluate the CSFs for management of the early stages of the PPVC project life cycle. Based on a comprehensive literature review and expert review, a list of the 9 CSFs relevant to the early stages of the PPVC project life cycle was established. Drawing on an online-based international questionnaire survey with global PPVC experts, the CSFs were measured. The dataset was statistically tested for reliability and analysed using several techniques such as mean scores, relativity weightings, and significance analysis.
Findings: The analysis revealed that the top 5 most influential CSFs for management of the early stages of the PPVC project life cycle include robust design specifications, accurate drawings and early design freeze; good working collaboration, effective communication and information sharing among project participants; effective stakeholder management; extensive project planning and scheduling; and early engagement of key players. The research further found correlations among the CSFs and proposed a conceptual framework for the management of the early stages of the PPVC project life cycle.
Research Limitations/Implications: The research recognizes that data quality and reliability risks are the major drawbacks of online questionnaire surveys but the engagement of experts with substantial theoretical and hands-on experiences in PPVC projects helped to minimize these risks. Although small, the sample size was justified and compared with studies that adopted the same data collection approach but analysed even smaller samples. However, the results should be interpreted against these limitations.
Practical Implications: The findings suggest that effective management of the early stages of the PPVC project lifecycle requires early commitment to the PPVC approach in a project; detailed planning and assessment of the suitability of PPVC for the given project; and collaborative design with manufacturers and suppliers to address module production challenges at the detailed design stage. These findings practically instructive and may serve as management-support during PPVC implementation.
Originality/Value: This research constitutes the first exclusive attempt at identifying the CSFs for successful management of the early stages of the PPVC project life cycle. It provides a fresh and more in-depth understanding of how best to manage the early stages of the PPVC project life cycle. Thus, it contributes to the practice and praxis of the PPVC project implementation discourse
Prefabrication‐based construction has several advantages, such as short building time and superior quality. The transportation of prefabricated products from factories to construction sites has two key issues to consider. One is how to efficiently utilize the capacity of trucks in order to use as few trucks as possible, and the other is how to postpone the transportation of prefabricated products so as to pay for them as late as possible. This study proposes a mathematical programming model to optimize the transportation planning of prefabricated products to minimize the sum of trucking transportation costs and inventory holding costs. Extensive numerical experiments show that the optimal transport plan generated by the model outperforms the plan obtained by a greedy approach by 10% of cost savings, implying the effectiveness of the model for the construction industry.
The use of prefabricated building systems offers considerable advantages in cases wherein extensive solutions to housing problems are immediately required. However, this system’s share in the overall building housing market in Libya is nearly negligible. This study attempts to explore the current situation of prefabricated building systems and their potential to address Libyan housing conditions. The perspectives of local experts in the construction industry are mainly considered. Qualitative analysis is conducted by using information obtained from interviews. Results show that prefabricated building can improve the Libyan housing industry; however, government and prospective practitioners who lack information, knowledge, and know-how of prefabricated building applications are often prejudiced against their use. Most of the interviewees also cannot fully provide conceptual or policy guidelines, which may serve as the starting point for the development of prefabricated building in Libya.
Purpose
This study applied the lean approach to the reinforcement work process in the component production of industrialised building system precast concrete construction (IBSPCC). The purpose of this paper is to identify and eliminate non-value added (NVA) activities to enhance the efficiency of the production process.
Design/methodology/approach
Data were collected via a case study of six-storey precast concrete building. A mapping of the reinforcement work process was conducted based on observations using time study technique and time-lapsed video, complemented by semi-structured interviews.
Findings
Through this application, several NVA activities, such as unnecessary inventory, excessive movement and coordination issues, were identified. Production performance could be enhanced by implementing Just-in-Time, Kanban, and layout improvements, which would address NVA activities.
Research limitations/implications
Due to the complexity of the construction process, only specific process elements were observed. To map the complete process, comprehensive observation must be conducted from beginning to end, which, though worthwhile, would be very time and resource intensive.
Originality/value
This paper focusses on strategies for improving the efficiency of the IBSPCC production process in Malaysian construction by developing a conceptual framework of the lean approach for the reinforcement work process. Certain aspects in the process such as layout and inventory need to be redesigned and simplified by minimising NVA activities.
The architecture, engineering and construction industry has long dealt with problems such as schedule and budget overruns, quality and safety issues, and low productivity. Off-site construction, which is a hybrid of manufacturing and construction, has significant potential to address industry’s endemic problems. However, off-site construction has been criticized for replicating the traditional subcontracting approach and therefore fragmented practice in the construction industry. The current research focuses on process integration and cross-training of multi-skilled resources as a solution to the aforementioned problem. To identify optimal process integration architectures for off-site construction, production data of three off-site manufacturers were analyzed by using a hybrid of fuzzy theory and the technique for order of preference by similarity to ideal solution. Findings reveal that process integration architectures transferring excess capacity from under-utilized to over-utilized resources in direct or indirect pathways are preferable in terms of satisfying decision criteria such as time and cost of cross-training, skill transferability, compliance with network logic, and safety considerations. The study contributes to the off-site construction literature by providing insight into dynamics of using multi-skilled resources. It also contributes to practice by developing a customizable and user-friendly framework for off-site production managers in order to identify the optimal process integration architecture in their own production scenarios.
There are two alternatives for production organization in precast factories-namely, the comprehensive method and the specialized method. Production scheduling under the specialized alternative has been found to be a difficult optimization problem if heterogeneous elements are involved. A flow shop sequencing model that incorporates actual constraints encountered in practice is proposed for this difficult case of precast production scheduling. The model is solved using a genetic algorithm (GA). The traditional minimize makespan and the more practical minimize tardiness penalty objective functions are optimized separately, as well as simultaneously using a normalized weighted GA. Comparisons between the GA and classical heuristic rules show that the GA can obtain good schedules for the model, giving a family of solutions that are at least as good as those produced by the use of heuristic rules.
Purpose
The purpose of this paper is to develop a model considering synergy effect for prefabricated construction service combination selection.
Design/methodology/approach
This research defines prefabricated construction service as a service-led construction method that meets the specific requirements of clients. Based on network theory, the multi-dimensional collaborative relationships of the prefabricated construction inter-services are formulated. The synergy effect is quantitatively calculated through the linear weighting of the strengths of collaborative relationships. Further, a weighted synergy network (WSN) is developed, from which a service composition selection model considering the synergy effect is established. Then, a genetic algorithm is employed to implement the model.
Findings
The results showed that (1) when the number of prefabricated construction services is increased, the synergy effect of combination options is enhanced; (2) The finer-grained prefabricated construction services, the stronger the synergy effect of service combination; (3) Clients have heterogeneous preferences for collaborative relationships, and there are differences in the synergy effect of service combination.
Originality/value
The contribution of this research includes proposed a method to quantify the synergy effect from the perspective of collaborative relationships, explored the specific procedure for the prefabricated construction service combination selection under the service-led construction, and provided a reference for promoting the development in construction. Besides, the model proposed could be applied to prefabricated construction service composition selection with diverse research boundaries or client preferences by executing the same procedure.
Purpose
For prefabricated building construction, improper handling of the production scheduling for prefabricated components is one of the main reasons that affect project performance, which causes overspending, schedule overdue and quality issues. Prior research on prefabricated components production schedule has shown that optimizing the flow shop scheduling problem (FSSP) is the basis for solving this issue. However, some key resources and the behavior of the participants in the context of actual prefabricated components production are not considered comprehensively.
Design/methodology/approach
This paper characterizes the production scheduling of the prefabricated components problem into a permutation flow shop scheduling problem (PFSSP) with multi-optimization objectives, and limitation on mold and buffers size. The lean construction principles of value-based management (VBM) and just-in-time (JIT) are incorporated into the production process of precast components. Furthermore, this paper applies biogeography-based optimization (BBO) to the production scheduling problem of prefabricated components combined with some improvement measures.
Findings
This paper focuses on two specific scenarios: production planning and production rescheduling. In the production planning stage, based on the production factor, this study establishes a multi-constrained and multi-objective prefabricated component production scheduling mathematical model and uses the improved BBO for prefabricated component production scheduling. In the production rescheduling stage, the proposed model allows real-time production plan adjustments based on uncertain events. An actual case has been used to verify the effectiveness of the proposed model and the improved BBO.
Research limitations/implications
With respect to limitations, only linear weighted transformations are used for objective optimization. In regards to research implications, this paper considers the production of prefabricated components in an environment where all parties in the supply chain of prefabricated components participate to solve the production scheduling problem. In addition, this paper creatively applies the improved BBO to the production scheduling problem of prefabricated components. Compared to other algorithms, the results show that the improved BBO show optimized result.
Practical implications
The proposed approach helps prefabricated component manufacturers consider complex requirements which could be used to formulate a more scientific and reasonable production plan. The proposed plan could ensure the construction project schedule and balance the reasonable requirements of all parties. In addition, improving the ability of prefabricated component production enterprises to deal with uncertain events. According to actual production conditions (such as the occupation of mold resources and storage resources of completed components), prefabricated component manufacturers could adjust production plans to reduce the cost and improve the efficiency of the whole prefabricated construction project.
Originality/value
The value of this article is to provide details of the procedures and resource constraints from the perspective of the precast components supply chain, which is closer to the actual production process of prefabricated components. In addition, developing the production scheduling for lean production will be in line with the concept of sustainable development. The proposed lean production scheduling could establish relationships between prefabricated component factory manufacturers, transportation companies, on-site contractors and production workers to reduce the adverse effects of emergencies on the prefabricated component production process, and promote the smooth and efficient operation of construction projects.
Purpose
This research aims to propose a comparative environmental analysis of conventional and prefabricated construction techniques utilizing a building information modelling (BIM) technique.
Design/methodology/approach
A set of indicators are selected to assess the environmental emissions throughout the construction life cycle, based on BIM platform. An existing project involving ten apartment buildings in Shanghai is selected as a case study.
Findings
The results reveal that prefabricated construction demonstrates environment-friendly performance with some exceptions of acidification and mineral resource consumption. Environmental impacts can also be further reduced by increasing the projected area ratio and percentage of project prefabrication.
Originality/value
Overall, the proposed method can be used to identify relevant environmental merits and for decision-making of appropriate construction techniques in building construction projects.
Purpose
Prefabricated construction concerns off-site production, multi-mode transportation and on-site installation of the prefabricated components, which are interdependent and dynamically interactive, so coordination among the multiple stages along the prefabricated component supply chain (PCSC) is indispensable. This study aims to solve the dynamic transportation planning problem for the PCSC by addressing the interdependency, dynamic interaction and coordination among the multiple stages and different objectives of the stakeholders.
Design/methodology/approach
The PCSC is analyzed and then the formulation for the dynamic transportation planning problem is developed based on the just-in-time (JIT) strategy. The particle swarm optimization (PSO) algorithm is applied to solve the dynamic optimization problem.
Findings
The proposed dynamic transportation planning method for the PCSC regarding component supplier selection, transportation planning for means, routes and schedule, site layout planning and transportation plan adjustment is able to facilitate coordination among the multiple stages by addressing their interdependencies and dynamic interactions, as well as different economic objectives of the stakeholders such as suppliers or the contractor.
Originality/value
The study helps to achieve the advantages of prefabricated construction by prompting coordination among multiple stages of the PCSC by realizing different benefits of the stakeholders. In addition, it provides the stakeholders with the competitive bidding prices and the evaluation data for the bids quote. Meanwhile, it contributes to the domain knowledge of the PCSC management with regard to the viewpoint of coordination and integration of multiple stages rather than only one stage as well as the dynamic optimization model based on the JIT strategy and the PSO algorithm.
Purpose
The purpose of this paper is to investigate the process optimization of a precast concrete component production line by using value stream mapping.
Design/methodology/approach
This paper is an empirical focused on of lean production theory and value stream mapping. The data in the case study were collected in real time on-site for each process during the production process of a prefabricated exterior wall.
Findings
The results of the current value stream map indicate that the main problems of the current production process are related to equipment, technology and organization. The equipment problems include simple demolding and cleaning tools and the lack of professional transfer channels. The technology problems include the lack of a marking mechanism and pipeline exit mechanism. There is a lack of standard operating procedures and incomplete process convergence. A comparison and analysis of the current value stream and the future value flow indicate that optimizations of the process flow, the production line layout, and the standard operating procedures have shortened the delivery cycle, reduced the number of workers, improved the operator’s operating level and balanced the production line.
Practical implications
The results of this study provide practitioners with a clear understanding of the optimization of the precast concrete component production and represent a method and basis for the process optimization of a factory production line; the approach is suitable for process optimization in other areas.
Originality/value
This research represents an innovative application of lean production theory and value stream mapping in a complex production line of precast concrete components and thereby fills the gap between the theory and practice of the optimization of a precast concrete component production line.
Purpose
Precast construction has become increasingly popular in the construction industry. Nonetheless, the logistics of construction materials has been a neglected topic, and this neglect has resulted in delays and cost overruns. Careful planning that considers all of the factors affecting construction logistics can ensure project success. The purpose of this paper is to examine the potential for using genetic algorithms (GAs) to derive logistics plans for materials production, supply and consumption.
Design/methodology/approach
The proposed GA model is based on the logistics of precast components from the supplier’s production yard, to the intermediate warehouse and then to the construction site. Using an activity-based costing (ABC) approach, the model not only considers the project schedule, but also takes into account the production and delivery schedule and storage of materials.
Findings
The results show that GAs are suitable for solving time-cost trade-off problems. The optimization process helps to identify the activity start time during construction and the delivery frequency that will result in the minimal cost. What-if scenarios can be introduced to examine the effects of changes in construction logistics on project outcomes.
Originality/value
This paper presents a method for using GAs and an ABC approach to support construction logistics planning decisions. It will help construction planners and materials suppliers to establish material consumption and delivery schedules, rather than relying on subjective judgment.
The paper explores the energy performances and environmental impacts of a prefabricated building module located in Messina (Sicily, Italy) through an approach that combines both the non-steady state building simulation and the Life Cycle Assessment methodology. The building uses renewable energy technologies and is usable in emergency situations or as simply temporary housing.
Results show that the building module causes the emission of 1.5 t of CO2eq/m² and consumes 29.2 GJ/m² of primary energy during its life cycle. The building achieves the Net Zero Energy Building target even if it has relevant environmental impacts in the materials production stage (72% on average of the total impacts while the use stage reaches the 23% on average). The construction and the end-of-life stages give a marginal contribution to the total impacts, since they account for the 1% and the 3%, respectively.
This paper addresses the problem of scheduling stochastic job shop subject to breakdown. A relative good and efficient genetic algorithm (GA) is proposed for the problem with normal processing time, resumable jobs and the objective of minimizing makespan. Some operations of normal processing times are defined to build the schedule. In the GA, an operation-based representation is used, a discrete event driven decoding method is presented to deal with breakdown and repair, and generalized order crossover and swap are applied to produce new solutions. Genetic operators are separate from the handling of random breakdown. The GA is applied to some test problems and compared with a simulated annealing (SA) and a particle swarm optimization (PSO). The computational results show the GA performs better than PSO and SA for stochastic job shop scheduling problems considered.
Examples of poor performance of precasters in terms of inefficient resource utilization and overstocking are commonplace in the precast industry. This is partly due to inaccurate planning practices and poor managerial decisions. The object of this paper is to develop a computer-based capacity planning model for precast concrete building products in order to help production managers to make better planning decisions and explore options open to them. The planning model is a factory simulator which automates the process of planning and predicts the effect of several managerial strategies before actual production commences. The performance of the model is examined using both real and hypothetical demand patterns. The paper has concluded that the model is a practical and considerable managerial tool for exploring and testing managerial options open to production managers. The model is suitable for companies which produce variety of concrete products on several plant. The authors welcome any collaboration with the industry to further the knowledge and application of the model. The model can be used to educate managers about the production process, the utilization of plant and the consequence of using certain managerial decisions.
There are two alternatives for production organisation in precast factories, namely the comprehensive method and the specialised method. Production scheduling under the specialised alternative has been found to be a difficult optimisation problem if heterogeneous elements are involved. A flow shop sequencing model is developed for this kind of production scheduling that considers the constraints encountered in actual practice. The model is optimised using a genetic algorithm (GA) approach. The results are compared with those obtained using classical heuristic rules in two examples that involve the objective of minimising the makespan or the total tardiness penalty. The comparison shows that the GA can obtain good schedules for the model, giving a family of solutions that are at least as good as those produced by the heuristic rules.
The goal of production scheduling is to achieve a profitable balance among on-time delivery, short customer lead time, and maximum utilization of resources. However, current practices in precast production scheduling are fairly basic, depending heavily on experience, thereby resulting in inefficient resource utilization and late delivery. Moreover, previous methods ignoring buffer size between stations typically induce unfeasible schedules. Certain computational techniques have been proven effective in scheduling. To enhance precast production scheduling, this research develops a multi-objective precast production scheduling model (MOPPSM). In the model, production resources and buffer size between stations are considered. A multi-objective genetic algorithm is then developed to search for optimum solutions with minimum makespan and tardiness penalties. The performance of the proposed model is validated by using five case studies. The experimental results show that the MOPPSM can successfully search for optimum precast production schedules. Furthermore, considering buffer sizes between stations is crucial for acquiring reasonable and feasible precast production schedules.