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.

Mathematical optimization approaches for facility layout problems: The state-of-the-art and future research directions

This work proposes a new methodology and mathematical formulation to address the facility layout problem.
The goal is to minimise the total material handling cost subjected to production-derived constraints. This cost is a function of the distance that the products should cover within the facility. The first idea is to use the $$ {\text{A}}^{ *} $$ algorithm to identify the distances between workstations in a more realistic way. $$ {\text{A}}^{ *} $$ determines the shortest path within the facility that contains obstacles and transportation routes. The second idea is to combine a genetic algorithm and the $$ {\text{A}}^{ *} $$ algorithm with a homogenous methodology to improve the quality of the facility layouts. In an iterative way, the layout solution space is explored using the genetic algorithm. We study the impacts of the appropriate crossover and mutation operators and the values of the parameters used in this algorithm on the cost of the proposed arrangements. These operators and parameter values are fine-tuned using Monte Carlo simulations. The facility arrangements are all compared and discussed based on their material handling cost associated with the Euclidean distance, rectilinear distance, and $$ {\text{A}}^{ *} $$ algorithm. Finally, we present a set of conclusions regarding the suggested methodology and discuss our future research goals.

/pdf/a-methodology-for-solving-facility-layout-problem-2hk9h62tk0.pdf

A methodology for solving facility layout problem considering barriers: genetic algorithm coupled with A* search

Optimizing consistency improvement of positive reciprocal matrices with implications for Monte Carlo Analytic Hierarchy Process

This paper proposes a three-phase framework to leverage hospital tracking data of patient visits while designing healthcare layouts with pod structures. The first phase proposes a process mining algorithm that modifies the Probabilistic Determining Finite Automata (PDFA) with Particle Swarm Optimization (PDFA-PSO) algorithm to predict the significant patient workflows from hospital historical data. The second phase employs simulation modeling to solve a right-sizing problem to determine the optimal size of the layout pods and the frequency of flows between the different clinical locations. The final phase uses an Unequal Area Facility Layout Problem (UAFLP) to determine the layout typology. The proposed process mining and simulation model are vital steps to measure the frequency between spaces and pod areas, which are needed to solve the UAFLP for outpatient settings. The proposed framework is validated using a case study for a renovation project of a large heart and vascular clinic in the US. The research shows that process mining is an efficient tool to extract a subset of significant patient pathways among 90 pathway variants and build a more realistic simulation that reflects behavioral and operational aspects. The research shows that the PSO algorithm is efficient in estimating the PDFA parameters and improving the prediction accuracy of the extracted patient pathways. In addition, the research shows that Genetic Algorithm with Placement Staretegy is an efficient algorithm for layout automation.

Integrated framework of process mining and simulation–optimization for pod structured clinical layout design

Integration of failure mode, effects, and criticality analysis with multi-criteria decision-making in engineering applications: Part II – Non-manufacturing industries

Facility layout aims to arrange a set of facilities in a site. The main objective function is to minimize the total material handling cost under production-derived constraints. This problem has received much attention during the past decades. However, these works have mainly focused on solving a 2D layout problem, dealing with the footprints of pieces of equipment. The obtained results have been then adapted to the real spatial constraints of a workshop. This research work looks to take account of spatial constraints within a 3D space from the very first steps of problem solving. The authors use a approach by combining a genetic algorithm with A*, 〈GA,A*〉 research. The genetic algorithm generates possible arrangements and A* finds the shortest paths that products must travel in a restricted 3D space. The application allows to converge to a layout minimizing the total material handling cost. This approach is illustrated by its application on an example inspired by a valve assembly workshop in Tunisia and the results are discussed from two points of view. The first one consists in comparing the effect of the choice of the distance measurement technique on the handling cost. For this purpose, the results of the application of 〈GA,A*〉 are compared with those obtained by combining the genetic algorithm and two of the most commonly used distance measurements in the literature of the discipline, namely the Euclidean distance, 〈GA,Euclidean〉, and the rectilinear distance, 〈GA,rectilinear〉. Our results show that the proposed approach offers better results than those of 〈GA,rectilinear〉 whereas they are not as good as those obtained by the 〈GA,Euclidean〉 approach. The effectiveness of the 〈GA,A*〉 approach is then studied from the perspective of the effect of the algorithm used for the generation of candidate arrangements. The final results obtained from the application of 〈GA,A*〉 are then compared with those of the approach combining particle swarm optimization and A*, 〈PSO,A*〉. This comparison shows that the 〈GA,A*〉 approach obtains better results. Nevertheless, its convergence speed is lower than that of 〈PSO,A*〉. The paper ends with some conclusions and perspectives.

3D facility layout problem

Multi-criteria decision making for the selection of a performant manual workshop layout: a case study

Facility Layout Problem (FLP) is concerned to arrange facilities efficiently within the available floor area in order to operate in an efficient way. So, the aim of this paper is to provide a survey related to the criteria that affect the effectiveness of a facility layout. The design criteria can be classified according to the previous research into two categories which are qualitative and quantitative indicators. Then, this paper presents a review of different Multi-Criteria Decision-Making (MCDM) techniques that have been proposed in the literature to pick the most suitable layout design. These methods are particularly suitable to deal with complex situations, including various criteria and conflicting goals which need to be optimized simultaneously. The review serves as a guide to those interested in how to evaluate and select the most appropriate layout which can handle an expanded range of manufacturing companies. Finally, we present a discussion followed by a conclusion.

/pdf/multi-criteria-decision-making-approaches-for-facility-30aiz86c2j.pdf

Multi-criteria Decision-Making Approaches for Facility Layout (FL) Evaluation and Selection: A Survey

Facility Layout Problem (FLP) is to arrange facilities efficiently within the available floor area to operate in an effective way. A good layout design contributes to the overall efficiency of operations. For this reason, in the FLP studies, design rules related to process flow, material handling, space shapes and requirements and communication between workers are taken into consideration. FLP has attracted much attention over last decades. However, as far as we were able to find, there is a lack of a survey that structures the used design rules, objectives functions, constraints and search strategies. In this paper, we aim at providing such study. Accordingly, an overview of the FLP is introduced based on basic features of the problem and resolution methodologies. We propose a new classification of FLP resolution methods according to objectives functions and constraints. Finally, we present an analysis and an assessment of the current and future trends of research in this field.

Mariem Besbes

Papers

A methodology for solving facility layout problem considering barriers: genetic algorithm coupled with A* search

3D facility layout problem

Multi-criteria decision making for the selection of a performant manual workshop layout: a case study

Multi-criteria Decision-Making Approaches for Facility Layout (FL) Evaluation and Selection: A Survey

A survey of different design rules-based techniques for facility layout problems