Management Science
The fuzzy approach to facilities layout problems
Fuzzy Sets and Systems
Genetic search and the dynamic facility layout problem
Computers and Operations Research - Special issue: heuristic, genetic and tabu search
A study of genetic crossover operations on the facilities layout problem
Computers and Industrial Engineering
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy development of crisp activity relationship charts for facilities layout
Computers and Industrial Engineering
Reasonable properties for the ordering of fuzzy quantities (I)
Fuzzy Sets and Systems
Pareto Simulated Annealing for Fuzzy Multi-Objective Combinatorial Optimization
Journal of Heuristics
Evolutionary approaches to the design and organization of manufacturing systems
Computers and Industrial Engineering
A genetic algorithm for facility layout problems of different manufacturing environments
Computers and Industrial Engineering
Fuzzy decision support system for manufacturing facilities layout planning
Decision Support Systems
Design of robust layout for Dynamic Plant Layout Problems
Computers and Industrial Engineering
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One of the problems encountered in the design of manufacturing systems is how to arrange the machines on the surface of the workshop, which is commonly referred to as a layout problem. Such a problem has been widely investigated in the literature. Most approaches use optimization technique to determine the position of each facility, assuming that the required data is available. Unfortunately, this assumption is often unrealistic, since the study design of a workshop is obviously conducted much before it is operating, so that data related to customer demands, for example, is generally not known with enough precision. Indeed, if good forecasts about what is to be produced in the next weeks can be available, they will obviously become more and more unreliable as the considered period of time will increase, so that layout found using classical approaches can turn out not to be relevant on the medium or long term. We propose an approach to design a robust layout in a context where the certainty of the information available decreases over time, which is usually the case for real applications. We propose a resolution approach based on a fuzzy evolutionary algorithm, which includes uncertain customer demands for each product. We show how this problem can be stated as a fuzzy dynamic layout problem with growing uncertainty over time. We suggest an evolutionary algorithm with adapted operators. Their performances are first tested using 2crisp layout problems already published. Then the impact of increasing uncertainty is studied using a suggested benchmark. The results of our experiments show the importance of considering the degradation of the information for designing robust layouts.