Heuristics for the dynamic facility layout problem with unequal area departments

The facility layout problem (FLP) is a well researched problem of finding positions of departments on a plant floor such that departments do not overlap and some objective(s) is (are) optimized. In this dissertation, the FLP with unequal area rectangular shaped departments is considered, when material flows between departments change during the planning horizon. This problem is known as the dynamic FLP. The change in material flows between pairs of departments in consecutive periods may require rearrangements of departments during the planning horizon in order to keep material handling costs low. The objective of our problem is to minimize the sum of the material handling and rearrangement costs. Because of the combinatorial structure of the problem, only small sized problems can be solved in reasonable time using exact techniques. As a result, construction and improvement heuristics are developed for the proposed problem. The construction algorithms are boundary search heuristics as well as a dual simplex method, and the improvement heuristics are tabu search and memetic heuristics with boundary search and dual simplex (linear programming model) techniques. The heuristics were tested on a generated data set as well as some instances from the literature. In summary, the memetic heuristic with the boundary search technique out-performed the other techniques with respect to solution quality

Overview of Dynamic Facility Layout Planning as a Sustainability Strategy

[EN] The facility layout design problem is significantly relevant within the business operations strategies framework and has emerged as an alternate strategy towards supply chain sustainability. However, its wide coverage in the scientific literature has focused mainly on the static planning approach and disregarded the dynamic approach, which is very useful in real-world applications. In this context, the present article offers a literature review of the dynamic facility layout problem (DFLP). First, a taxonomy of the reviewed papers is proposed based on the problem formulation current trends (related to the problem type, planning phase, planning approach, number of facilities, number of floors, number of departments, space consideration, department shape, department dimensions, department area, and materials handling configuration); the mathematical modeling approach (regarding the type of model, type of objective function, type of constraints, nature of market demand, type of data, and distance metric), and the considered solution approach. Then, the extent to which recent research into DFLP has contributed to supply chain sustainability by addressing its three performance dimensions (economic, environmental, social) is described. Finally, some future research guidelines are provided.This research was funded by the Spanish Ministry of Science, Innovation and Universities Project CADS4.0, grant number RTI2018-101344-B-I00; and the Valencian Community ERDF Programme 2014-2020, grant number IDIFEDER/2018/025.Pérez-Gosende, P.; Mula, J.; Díaz-Madroñero Boluda, FM. (2020). Overview of Dynamic Facility Layout Planning as a Sustainability Strategy. Sustainability. 12(19):1-16. https://doi.org/10.3390/su12198277S1161219Ghassemi Tari, F., & Neghabi, H. (2015). A new linear adjacency approach for facility layout problem with unequal area departments. Journal of Manufacturing Systems, 37, 93-103. doi:10.1016/j.jmsy.2015.09.003Kheirkhah, A., Navidi, H., & Messi Bidgoli, M. (2015). Dynamic Facility Layout Problem: A New Bilevel Formulation and Some Metaheuristic Solution Methods. IEEE Transactions on Engineering Management, 62(3), 396-410. doi:10.1109/tem.2015.2437195Altuntas, S., & Selim, H. (2012). 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A new intelligent algorithm for dynamic facility layout problem in state of fuzzy constraints. Neural Computing and Applications, 24(5), 1179-1190. doi:10.1007/s00521-013-1339-5KIA, R., JAVADIAN, N., PAYDAR, M. M., & SAIDI-MEHRABAD, M. (2013). A SIMULATED ANNEALING FOR INTRA-CELL LAYOUT DESIGN OF DYNAMIC CELLULAR MANUFACTURING SYSTEMS WITH ROUTE SELECTION, PURCHASING MACHINES AND CELL RECONFIGURATION. Asia-Pacific Journal of Operational Research, 30(04), 1350004. doi:10.1142/s0217595913500048Mazinani, M., Abedzadeh, M., & Mohebali, N. (2012). Dynamic facility layout problem based on flexible bay structure and solving by genetic algorithm. The International Journal of Advanced Manufacturing Technology, 65(5-8), 929-943. doi:10.1007/s00170-012-4229-6Samarghandi, H., Taabayan, P., & Behroozi, M. (2013). Metaheuristics for fuzzy dynamic facility layout problem with unequal area constraints and closeness ratings. 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Facility layout problem: Bibliometric and benchmarking analysis

Facility layout problem is related to the location of departments in a facility area, with the aim of determining the most effective configuration. Researches based on different approaches have been published in the last six decades and, to prove the effectiveness of the results obtained, several instances have been developed. This paper presents a general overview on the extant literature on facility layout problems in order to identify the main research trends and propose future research questions. Firstly, in order to give the reader an overview of the literature, a bibliometric analysis is presented. Then, a clusterization of the papers referred to the main instances reported in literature was carried out in order to create a database that can be a useful tool in the benchmarking procedure for researchers that would approach this kind of problems

Metaheuristics for the Generalized Quadratic Assignment Problem

The generalized quadratic assignment problem (GQAP) is the task of assigning a set of facilities to a set of locations such that the sum of the assignment and transportation costs is minimized. The facilities may have different space requirements, and the locations may have varying space capacities. Also, multiple facilities may be assigned to each location such that space capacity is not exceeded. In this research, an application of the GQAP is presented for assigning a set of machines to a set of locations on the plant floor. Two meta-heuristics are proposed for solving the GQAP: tabu search (TS) and simulated annealing (SA). In addition, two types of neighborhood structures are considered for each meta-heuristic. A set of 21 test problems, available in the literature, is used to evaluate the performances of the meta-heuristics using one or two neighborhood structures. Computational experiments show that the proposed SA heuristics performed better than the proposed TS heuristics. The SA heuristics obtained results better than those presented in the literature for three of the test problems. On the other hand, the TS heuristics did not perform well for the problems with high space capacity utilization

Ant colony heuristics for the dynamic facility layout problem

As global economic competition and cooperation become more and more drastic, the enterprise\u27s facility layout needs to be more flexible to adapt to the rapidly changing environment. Therefore, attention should be given to the dynamical nature of the facility layout. In other words, the flow of materials between departments changes during the planning horizon (multiple periods) and should be considered. This problem is known as the dynamic facility layout problem (DFLP).;This research proposes three heuristics based on the ant colony optimization (ACO) heuristic to solve the DFLP. The performance of the heuristics was evaluated using two data sets taken from the literature. Results obtained show that the proposed heuristics are effective for the dynamic facility layout problem

Heuristics and Metaheuristics Approaches for Facility Layout Problems: A Survey

Facility Layout Problem (FLP) is a NP-hard problem concerned with the arrangement of facilities as to minimize the distance travelled between all pairs of facilities. Many exact and approximate approaches have been proposed with an extensive applicability to deal with this problem. This paper studies the fundamentals of some well-known heuristics and metaheuristics used in solving the FLPs. It is hoped that this paper will trigger researchers for in-depth studies in FLPs looking into more specific interest such as equal or unequal FLPs

ARCH: a Robust Construction Heuristic for the Layout Design of Food Processing Facilities.

A Robust Construction Heuristic (ARCH) represents the first attempt to develop a facilities layout design algorithm tailored to the particular solution of the food processing facility layout problem where a fluctuating product mix due to seasonality or changes in consumer demand is typical. The foundation literature for this research comes predominantly from the industrial engineering, management science, and food science fields. Construction heuristics built layouts from scratch and provided poor quality results. Robustness algorithms had no simplifying heuristics but were reported to yield potentially higher quality layouts than traditional algorithms for layout problems with fluctuating product mixes. ARCH was developed as an alternative layout design algorithm based on the parallel philosophies that a robustness consideration would improve the relatively low quality solutions reported for construction heuristics and that a construction approach would allow the robust algorithm to be realistically implemented. ARCH was found to provide layout solutions comparable to or better than improvement heuristics for benchmark problems from the literature. A case study of an existing ham processing line was performed and a layout design for the plant generated by ARCH. In-plant surveys were conducted to develop pertinent input data for ARCH. Three products, whole smoked ham, chunked-and-formed ham, and pork sausage were produced by the plant. Historical seasonal demands were used for the expected fluctuation in levels of demand for each product. Certain assumptions had to be made to allow ARCH to consider layouts with certain flow patterns (U-shaped). The resulting layout designs were rather unorthodox in shape but could be used by the human designer to determine adjacency requirements for the final design

New Mixed Integer Programming for Facility Layout Design without Loss of Department Area

This paper proposes a New Mixed Integer Programming (NMIP) for solving facility layout problem (FLP). The formulation is extensively tested on problems from literature to minimize material handling cost when addresses on the shop floor. Every department and shop floor in tested problem were fixed dimension of length and width. Classic Mixed Integer Programming (MIP) solves FLP with fixed layout area and preset each department’s lower-upper limit of length and width. As a result, there might be some departments with 5-10% area less than initial layout design requirements which leads to problem in design and construction process. It is infeasible to address the department on the actual shop floor thus adjustment of result from MIP is required. The main purpose of NMIP is to eliminate such infeasibility and show the efficiency of this model. Keywords: mixed integer programing, facility layout design, facility layout problem, heuristic