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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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

Dynamic Facility Layout for Cellular and Reconfigurable Manufacturing using Dynamic Programming and Multi-Objective Metaheuristics

The facility layout problem is one of the most classical yet influential problems in the planning of production systems. A well-designed layout minimizes the material handling costs (MHC), personnel flow distances, work in process, and improves the performance of these systems in terms of operating costs and time. Because of this importance, facility layout has a rich literature in industrial engineering and operations research. Facility layout problems (FLPs) are generally concerned with positioning a set of facilities to satisfy some criteria or objectives under certain constraints. Traditional FLPs try to put facilities with the high material flow as close as possible to minimize the MHC. In static facility layout problems (SFLP), the product demands and mixes are considered deterministic parameters with constant values. The material flow between facilities is fixed over the planning horizon. However, in today’s market, manufacturing systems are constantly facing changes in product demands and mixes. These changes make it necessary to change the layout from one period to the other to be adapted to the changes. Consequently, there is a need for dynamic approaches of FLP that aim to generate layouts with high adaptation concerning changes in product demand and mix. This thesis focuses on studying the layout problems, with an emphasis on the changing environment of manufacturing systems. Despite the fact that designing layouts within the dynamic environment context is more realistic, the SFLP is observed to have been remained worthy to be analyzed. Hence, a math-heuristic approach is developed to solve an SFLP. To this aim, first, the facilities are grouped into many possible vertical clusters, second, the best combination of the generated clusters to be in the final layout are selected by solving a linear programming model, and finally, the selected clusters are sequenced within the shop floor. Although the presented math-heuristic approach is effective in solving SFLP, applying approaches to cope with the changing manufacturing environment is required. One of the most well-known approaches to deal with the changing manufacturing environment is the dynamic facility layout problem (DFLP). DFLP suits reconfigurable manufacturing systems since their machinery and material handling devices are reconfigurable to encounter the new necessities for the variations of product mix and demand. In DFLP, the planning horizon is divided into some periods. The goal is to find a layout for each period to minimize the total MHC for all periods and the total rearrangement costs between the periods. Dynamic programming (DP) has been known as one of the effective methods to optimize DFLP. In the DP method, all the possible layouts for every single period are generated and given to DP as its state-space. However, by increasing the number of facilities, it is impossible to give all the possible layouts to DP and only a restricted number of layouts should be fed to DP. This leads to ignoring some layouts and losing the optimality; to deal with this difficulty, an improved DP approach is proposed. It uses a hybrid metaheuristic algorithm to select the initial layouts for DP that lead to the best solution of DP for DFLP. The proposed approach includes two phases. In the first phase, a large set of layouts are generated through a heuristic method. In the second phase, a genetic algorithm (GA) is applied to search for the best subset of layouts to be given to DP. DP, improved by starting with the most promising initial layouts, is applied to find the multi-period layout. Finally, a tabu search algorithm is utilized for further improvement of the solution obtained by improved DP. Computational experiments show that improved DP provides more efficient solutions than DP approaches in the literature. The improved DP can efficiently solve DFLP and find the best layout for each period considering both material handling and layout rearrangement costs. However, rearrangement costs may include some unpredictable costs concerning interruption in production or moving of facilities. Therefore, in some cases, managerial decisions tend to avoid any rearrangements. To this aim, a semi-robust approach is developed to optimize an FLP in a cellular manufacturing system (CMS). In this approach, the pick-up/drop-off (P/D) points of the cells are changed to adapt the layout with changes in product demand and mix. This approach suits more a cellular flexible manufacturing system or a conventional system. A multi-objective nonlinear mixed-integer programming model is proposed to simultaneously search for the optimum number of cells, optimum allocation of facilities to cells, optimum intra- and inter-cellular layout design, and the optimum locations of the P/D points of the cells in each period. A modified non-dominated sorting genetic algorithm (MNSGA-II) enhanced by an improved non-dominated sorting strategy and a modified dynamic crowding distance procedure is used to find Pareto-optimal solutions. The computational experiments are carried out to show the effectiveness of the proposed MNSGA-II against other popular metaheuristic algorithms

The Single Row Facility Layout Problem: State of the Art

The single row facility layout problem (SRFLP) is a NP-hard problem concerned with the arrangement of facilities of given lenghs on a line so as to minimize the weighted sum of the distances between all the pairs of facilities. The SRFLP and its special cases often arise while modeling a large variety of applications. It was actively researched until the mid-nineties. It has again been actively studied since 2005. Interestingly, research on many aspects of this problem is still in the initial stages, and hence the SRFLP is an interesting problem to work on. In this paper, we review the literature on the SRFLP and comment on its relationship with other location problems. We then provide an overview of different formulations of the problem that appear in the literature. We provide exact and heuristic approaches that have been used to solve SRFLPs, and finally point out research gaps and promising directions for future research on this problem.

Hybrid approach of discrete event simulation integrated with location search algorithm in a cells assignment problem: a case study

[EN] This paper presents a case study describing a cell assignment problem in an assembly facility. These cells receive parts from external suppliers, and sort and sequence these parts to feed the final assembly line. Therefore, to each cell are associated important inbound and outbound flows generating hundreds of material handling equipment movements along the facility, impacting the traffic density and causing eventually safety issues in the plant. Following an important plant redesign, cells have been relocated, and the plant managers need to decide how to manage the new logistic flows. To that aim, a hybrid approach encompassing mathematical optimization and discrete event simulation (DES) is proposed. This approach allows us to reduce complexity by decomposing the design into two phases. The first phase deals with the problem of generating cell¿s assignment alternatives by using a heuristic method to find good quality solutions. 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Tabu Search for the Single Row Facility Layout Problem in FMS using a 3-opt Neighborhood

Since material handling agents in a FMS are most efficient when moving in straight lines, a common layout of machines in a FMS is a single row layout. This allows a floor designer to model the problem of generating an optimal machine layout in a FMS as a single row facility layout problem (SRFLP). Due to the computational complexity involved in solving the SRFLP, researchers have developed several heuristics to solve large instances of the problem. In this paper, we present a tabu search implementation based on a 3-opt neighborhood search scheme. We also present a technique to speed up the exhaustive 3-opt neighborhood search process significantly. Our computational experiments show that speed up of the 3-opt search is effective, and our tabu search implementation is competitive. The results we present here are better than the currently known best layouts for several large sized benchmark SRFLP instances, and competitive for other benchmark instances.

A Lin-Kernighan Heuristic for Single Row Facility Layout

The single row facility layout problem (SRFLP) is the problem of arranging facilities with given lengths on a line, while minimizing the weighted sum of the distances between all pairs of facilities. The problem is known to be NP-hard. In this paper, we present a neighborhood search heuristic called LK-INSERT which uses a Lin-Kernighan neighborhood structure built on insertion neighborhoods. To the best of our knowledge this is the first such heuristic for the SRFLP. Our computational experiments show that LK-INSERT is competitive and improves the best known solutions for several large sized benchmark SRFLP instances.