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A Data-driven Approach to Enhance Worker Productivity by Optimizing Facility Layout
Owing to the dramatic increase of the individualized demand, mass customization has become a mainstream production mode with product demand uncertainty, which leads to logistics uncertainties at each production stage. To handle these different types of uncertainties, a hybrid robust optimization model for unequal-area dynamic facility layout problem (UA-DFLP) considering the location of pick-up and drop-off points (P/D points) is proposed. Furthermore, an improved particle swarm optimization (PSO) algorithm is developed to solve the proposed model. A real case acquired from an assembly line demonstrates the effectiveness of the approach.
The shortest path problem is one of the most classical algorithm issues in graph theory, aiming to find the shortest path between the two nodes in a network. It is widely used to solving the path search problems in the relevant application, including network routing algorithm, artificial intelligence, game design, and so on. This paper introduces three basic algorithms and compares them theoretically by analyzing the time and space complexity. Then, the paper discusses their performances and summarizes the best application range. At last it introduces applications of shortest path algorithm.
Facility layout problem (FLP) is defined as the placement of facilities in a plant area, with the aim of determining the most effective arrangement in accordance with some criteria or objectives under certain constraints, such as shape, size, orientation, and pick-up/drop-off point of the facilities. It has been over six decades since Koopmans and Beckmann published their seminal paper on modeling the FLP. Since then, there have been improvements to these researchers’ original quadratic assignment problem. However, research on many aspects of the FLP is still in its initial stage; hence, the issue is an interesting field to work on. Here, a review of literature is made by referring to numerous papers about FLPs. The study is mainly motivated by the current and prospective trends of research on such points as layout evolution, workshop characteristics, problem formulation, and solution methodologies. It points to gaps in the literature and suggests promising directions for future research on FLP.
This paper describes a procedure that can be used by facility designers to allocate space to manufacturing cells. The procedure takes into consideration the area and shape requirements of individual cells as well as any occupied regions on a floor plan. A layout is represented as a collection of rectangular partitions organized as a slicing tree. The solution method involves searching through the space of all slicing trees of a given structure. An effective simulated annealing algorithm capable of minimizing inter-cell traffic flow and enforcing geometric constraints is presented. The algorithm is compared with two local search methods with encouraging results.
Layout design and material handling system design are two of the major aspects of facility planning. Although both aspects directly influence each other, the classical approach to the layout design is carried out in two separate steps: in the first step the block layout, i.e. the location of the departments in the workshop, is constructed, and in the second step, the material handling system is designed. The separate optimisation of these two aspects of the problem leads to solutions that can be far from the global optimum. In this paper, we develop an integrated algorithm to design the facilities and material handling systems. We focus on single-loop AGV systems. The proposed algorithm determines the block layout, AGV single-loop flow path and pick-up delivery stations, simultaneously. The associated from–to chart and the area of departments are the principal inputs of the algorithm. The objective is minimising total material flow distance among all departments. The results of our computational experiments show the algorithm was coded using MATLAB 7.0, and that our integrated algorithm is more efficient in terms of both the objective function value and the runtime.
Here, an attempt is made to present a state-of-the-art review of papers on facility layout problems. This paper aims to deal
with the current and future trends of research on facility layout problems based on previous research including formulations,
solution methodologies and development of various software packages. New developments of various techniques provide a perspective
of the future research in facility layout problems. A trend toward multi-objective approaches, developing facility layout
software using meta-heuristics such as simulated annealing (SA), genetic algorithm (GA) and concurrent engineering to facility
layout is observed.
This paper presents an intuitive, simple and efficient simulated annealing searching technique to solve non-guillotine, two- or three-dimensional cutting stock problems. This algorithm considers the possibility of placing different sizes of small rectangles or boxes on a larger rectangle (pallet) or container, in such a way that the amount of trim loss is minimized. The algorithm we propose provides a basis for exploring the integration of the simulated annealing technique with artificial intelligence, and interval algebra. The algorithm is programmed in C and run on a personal computer with an Intel 486-based CPU. The algorithm is tested using randomly generated test cases and also using real data from a printing company in Hong Kong.
This paper discusses the notion of workflow congestion in the context of material handling equipment interruptions in a manufacturing or warehousing facility. Development of a combination of probabilistic and physics-based models for workflow interruptions permits evaluation of the expected link travel time. The problem is then of routing in a way that minimizes total expected travel time. The rerouting problem is modeled as a multicommodity flow problem with link capacity design. A greedy upper bounding and Lagrangean relaxation algorithm are developed to solve this efficiently. To calibrate our modeling process we develop an object-oriented simulation model that explicitly considers various workflow interruptions. Our major finding is that rerouting traffic in a congested facility can significantly alleviate congestion delays and improve the efficiency of material movement. A managerial insight derived from this work is that rerouting is most effective in medium traffic-intensity situations.
Industry 4.0 connotes a new industrial revolution centered around cyber-physical systems. It posits that the real-time connection of physical and digital systems, along with new enabling technologies, will change the way that work is done and therefore, how work should be managed. It has the potential to break, or at least change, the traditional operations trade-offs among the competitive priorities of cost, flexibility, speed, and quality. This article describes the technologies inherent in Industry 4.0 and the opportunities and challenges for research in this area. The focus is on goods-producing industries, which includes both the manufacturing and agricultural sectors. Specific technologies discussed include additive manufacturing, the internet of things, blockchain, advanced robotics, and artificial intelligence.
The designer of a plant layout is faced with the efficient arrangement of facilities, the planning of material handling locations, and the aisle design. These mutually dependent subproblems are traditionally solved in a sequential process. Designing the material flow paths within the arranged facilities can be difficult and the expected material flow distances between the arranged facilities can be exceeded significantly. Also, when the aisle design is not known, the area between facilities is difficult to estimate and might require costly replanning. The purpose of this study is to investigate the advantage of an integrated planning of these subproblems using a holistic view. We propose two models in this paper. The first is a mixed integer linear programming formulation for concurrently solving small-sized facility layout problems, including the material handling points, and the path design. In a second model aisles are implemented instead of paths, which is a scarcely considered design aspect within the related literature. Several sets of valid inequalities are proposed to shorten the solution time. To compare the solution quality between the proposed integrated approaches and traditional approaches, a comprehensive computational study has been conducted considering several influencing design factors. The results indicate that the integrated planning of the layout and the material handling network design is a large untapped potential for designing superior layout solutions and facilitating the planning process.
Facility layout problems are an important class of operations research problems that has been studied for several decades. Most variants of facility layout are NP-hard, therefore global optimal solutions are difficult or impossible to compute in reasonable time. Mathematical optimization approaches that guarantee global optimality of solutions or tight bounds on the global optimal value have nevertheless been successfully applied to several variants of facility layout. This review covers three classes of layout problems, namely row layout, unequal-areas layout, and multifloor layout. We summarize the main contributions to the area made using mathematical optimization, mostly mixed integer linear optimization and conic optimization. For each class of problems, we also briefly discuss directions that remain open for future research.
Single floor facility layout problem (FLP) is related to finding the arrangement of a given number of departments within a facility; while in multi-floor FLP, the departments should be imbedded in some floors inside the facility. The significant influence of layout design on the effectiveness of any organization has turned FLP into an important issue. This paper presents a three- (two-) stage mathematical programming method to find competitive solutions for multi- (single-) floor problems. At the first stage, the departments are assigned to the floors through a mixed integer programming model (the single floor version does not require this stage). At the second stage, a nonlinear programming model is used to specify the relative position of the departments on each floor; and at the third stage, the final layouts within the floors are determined, through another nonlinear programming model. The multi-floor version is studied in the states in which the locations of the elevators are either formerly specified or not. Computational results show that this framework can find a wide variety of high quality layouts at competitive cost (up to 43% reduction) within a short amount of time for small and especially large size problems, compared to the existing methods in the literature. Also, the proposed method is flexible enough to accommodate the complicated and real-world problems, because of using mathematical programming model and solving it directly.
This chapter introduces a comprehensive modelling framework for integrating layout design and material flow network design toward the direct generation of net layouts including the design of the physical aisle system. Eight models are developed, each being specialized to deal with various facets of this integrated design. The framework offers an alternative conceptual platform to the Quadratic Assignment Problem for layout design researchers.
This paper presents a biased random-key genetic algorithm (BRKGA) for the unequal area facility layout problem (UA-FLP) where a set of rectangular facilities with given area requirements has to be placed, without overlapping, on a rectangular floor space. The objective is to find the location and the dimensions of the facilities such that the sum of the weighted distances between the centroids of the facilities is minimized. A hybrid approach combining a BRKGA, to determine the order of placement and the dimensions of each facility, a novel placement strategy, to position each facility, and a linear programming model, to fine-tune the solutions, is developed. The proposed approach is tested on 100 random datasets and 28 of benchmark datasets taken from the literature and compared with 21 other benchmark approaches. The quality of the approach was validated by the improvement of the best known solutions for 19 of the 28 extensively studied benchmark datasets.
In this paper we present a facility layout algorithm that iterates between a genetic algorithm with a slicing tree representation and a mixed-integer program with a subset of the binary variables set via the genetic algorithm. The genetic algorithm is very good at finding low-cost solutions while maintaining shape constraints on the departments. The slicing tree representation and the mixed-integer program are compatible in terms of layout representation, with the mixed-integer program representation more general. The mixed-integer program allows us to relax the last remaining constraints of the slicing tree representation of the genetic algorithm. We present our genetic algorithm and the iterative algorithm, while illustrating their performance on test problems from the literature. In 10 of the 12 problems, new lower best-cost solutions are found.
Self-storage is a booming industry. Both private customers and companies can rent temporary space from such facilities. The design of self-storage warehouses differs from other facility designs in its focus on revenue maximization. A major question is how to design self-storage facilities to fit market segments and accommodate volatile demand to maximize revenue. Customers that cannot be accommodated with a space size of their choice can be either rejected or upscaled to a larger space. Based on data of 54 warehouses in America, Europe, and Asia, we propose a new facility design approach with models for three different cases: an overflow customer rejection model and two models with customer upscale possibilities, one with reservation and another without reservation. We solve the models for several real warehouse cases, and our results show that the existing self-storage warehouses can be redesigned to generate larger revenues for all cases. Finally, we show that the upscaling policy without reservation generally outperforms the upscaling policy with reservation.
This paper presents an integrated approach for the facilities design problem. It develops a method for the concurrent determination of the block layout, the locations of departmental input and output (I/O) points using the contour distances between the I/O points, and the material flow paths between the I/O points. The topology of block layouts is represented using two linear sequences (sequence-pair), which allows the layout to have either a slicing or a non-slicing structure. The block layout is obtained from the sequence-pair with a linear programming formulation. Three heuristic methods are then presented to determine for a given block layout the locations of the I/O points on the perimeters of the departments. The flow paths from output to input points are found by determining the shortest paths that follow the perimeters of the departments. The linear programming algorithm, the shortest path algorithm, and the I/O point location heuristics are embedded into a simulated annealing algorithm that modifies the sequence-pair to obtain a high-quality layout based on the contour distances between the I/O points. Results of computational experiments show that the performance of this integrated algorithm compares favourably with those of algorithms using a sequential approach and is capable of solving industrial-sized problems in acceptable computation time.
We consider the problem of locating input and output (I/O) points of each department for a given layout. The objective of the problem is to minimise the total distance of material flows between the I/O points. Here, distances between the I/O points are computed as the lengths of the shortest path (not the rectilinear distances) between the I/O points. We developed a procedure to eliminate dominated candidate positions of I/O points that do not need to be considered. With this procedure, a large number of dominated candidate positions can be eliminated. A linear programming (LP) model for minimising the total rectilinear distance of flows is used to obtain a lower bound. Using the elimination procedure and the LP model, a branch and bound algorithm is developed to find an optimal location of the I/O points. Results from computational experiments show that the suggested algorithm finds optimal solutions in a very short time even for large-sized problems.
A model ia described which can be used to assist in the design of a facility, where the facilities design includes the selection of the materials handling system and the placement of departments within the facility. The model is entitled COFAD, an acronym representing Computerized FAcilities Design. COFAD selects the facilities design which approaches the minimal materials handling system cost. The input requirements and the utilization of COFAD are demonstrated via an example problem. Although it is shown that the model results in good solutions, due to the complexity of the design problem, no claim of optimality can be made.
In this paper we introduce the use of spacefilling curves in facility layout, and we extend a well-known facility layout algorithm () to facilities with multiple floors. Spacefilling curves make it possible to exchange any two departments and to use more powerful exchange routines than two-way or three-way exchanges. We also further enhance CRAFT by controlling department shapes, and (with multiple floors) by allowing "flexible" departmental area requirements. Although the algorithm we present can be used for any single-floor or multi-floor facility layout problem, its primary target is production facilities. A tailored version of the algorithm was successfully tested and used in a large, multi-floor production facility. The algorithm differs significantly from two previous extensions of to multi-floor facilities.
Layout problems are found in several types of manufacturing systems. Typically, layout problems are related to the location of facilities (e.g., machines, departments) in a plant. They are known to greatly impact the system performance. Most of these problems are NP hard. Numerous research works related to facility layout have been published. A few literature reviews exist, but they are not recent or are restricted to certain specific aspects of these problems. The literature analysis given here is recent and not restricted to specific considerations about layout design.We suggest a general framework to analyze the literature and present existing works using such criteria as: the manufacturing system features, static/dynamic considerations, continual/discrete representation, problem formulation, and resolution approach. Several research directions are pointed out and discussed in our conclusion.
To achieve high productivity in a flexible manufacturing system (FMS), an efficient layout arrangement and material flow path design are important due to the large percentage of product cost that is related to material handling. The layout design problem addressed in this paper has departments with fixed shapes and pick-up/drop-off points. It is an open-field type layout with single-loop directed flow path. A two-step heuristic is proposed to solve the problem. It first solves a traditional block layout with directed-loop flow path to minimize material handling costs by using a combined spacefilling curve and simulated annealing algorithm. The second step of the proposed methodology uses the resulting flow sequence and relative positioning information from the first step as input to solve the detailed FMS layout, which includes the spatial coordinates and orientation of each FMS cell. This detailed FMS layout problem is formulated and solved as a mixed integer program. Empirical illustrations show promising results for the proposed methodology in solving real-world type problems.
The paper discusses the application of an evolutionary computation technique for the design of efficient facilities. Genetic algorithms (GA) have been applied to heuristically solve a number of combinatorial problems such as scheduling, the traveling salesman problem and the quadratic assignment problem. We apply GA to the layout problem which arises frequently in the design of manufacturing and service organizations to find “good” solutions.In this paper we outline a GA based algorithm for solving the single-floor facility layout problem. We consider departments of both equal and unequal sizes. The GAs performance is evaluated using several test problems available in the literature. The results indicate that GA may provide a better alternative in a realistic environment where the objective is to find a number of “reasonably good” layouts. The implementation also provides the flexibility of having fixed departments and to interactively modify the layouts produced.
In a recent paper, Savas et al. [S. Savas, R. Batta, R. Nagi, Finite-size facility placement in the presence of barriers to rectilinear travel, Operations Research 50 (6) (2002) 1018–1031] consider the optimal placement of a finite-sized facility in the presence of arbitrarily shaped barriers under rectilinear travel. Their model applies to a layout context, since barriers can be thought to be existing departments and the finite-sized facility can be viewed as the new department to be placed. In a layout situation, the existing and new departments are typically rectangular in shape. This is a special case of the Savas et al. paper. However the resultant optimal placement may be infeasible due to practical constraints like aisle locations, electrical connections, etc. Hence there is a need for the development of contour lines, i.e. lines of equal objective function value. With these contour lines constructed, one can place the new facility in the best manner. This paper deals with the problem of constructing contour lines in this context. This contribution can also be viewed as the finite-size extension of the contour line result of Francis [R.L. Francis, Note on the optimum location of new machines in existing plant layouts, Journal of Industrial Engineering 14 (2) (1963) 57–59].
In this paper we present a general genetic algorithm to address a wide variety of sequencing and optimization problems including multiple machine scheduling, resource allocation, and the quadratic assignment problem. When addressing such problems, genetic algorithms typically have difficulty maintaining feasibility from parent to offspring. This is overcome with a robust representation technique called random keys. Computational results are shown for multiple machine scheduling, resource allocation, and quadratic assignment problems.
INFORMS Journal on Computing, ISSN 1091-9856, was published as ORSA Journal on Computing from 1989 to 1995 under ISSN 0899-1499.
Random-key genetic algorithms were introduced by Bean (ORSA J. Comput. 6:154–160, 1994) for solving sequencing problems in combinatorial optimization. Since then, they have been extended to handle a wide class
of combinatorial optimization problems. This paper presents a tutorial on the implementation and use of biased random-key
genetic algorithms for solving combinatorial optimization problems. Biased random-key genetic algorithms are a variant of
random-key genetic algorithms, where one of the parents used for mating is biased to be of higher fitness than the other parent.
After introducing the basics of biased random-key genetic algorithms, the paper discusses in some detail implementation issues,
illustrating the ease in which sequential and parallel heuristics based on biased random-key genetic algorithms can be developed.
A survey of applications that have recently appeared in the literature is also given.
The facility layout problem (FLP) is a fundamental optimization problem encountered in many manufacturing and service organizations. Montreuil introduced a mixed integer programming (MIP) model for FLP that has been used as the basis for several rounding heuristics. However, no further attempt has been made to solve this MIP optimally. In fact, though this MIP only has 2n(n−1) 0–1 variables, it is very difficult to solve even for instances with n≈5 departments. In this paper we reformulate Montreuil’s model by redefining his binary variables and tightening the department area constraints. Based on the acyclic subgraph structure underlying our model, we propose some general classes of valid inequalities. Using these inequalities in a branch-and-bound algorithm, we have been able to moderately increase the range of solvable problems. We are, however, still unable to solve problems large enough to be of practical interest. The disjunctive constraint structure underlying our FLP model is common to several other ordering/arrangement problems; e.g., circuit layout design, multi-dimensional orthogonal packing and multiple resource constrained scheduling problems. Thus, a better understanding of the polyhedral structure of this difficult class of MIPs would be valuable for a number of applications.
http://deepblue.lib.umich.edu/bitstream/2027.42/3481/5/ban1152.0001.001.pdf http://deepblue.lib.umich.edu/bitstream/2027.42/3481/4/ban1152.0001.001.txt
Solving the facility layout problem with BLOCPLAN
- C Donaghey
- V Pire
Donaghey, C. and V. Pire (1990). Solving the facility layout problem with BLOCPLAN.
MICRO-CRAFT program documentation
- Y Hosni
- G Whitehouse
- T Atkins
Hosni, Y., G. Whitehouse, and T. Atkins (1980). MICRO-CRAFT program documentation.