Modeling, Exact Solution and Algorithmic Comparison of the Single-Row Facility Layout Problem with Fuzzy-Random Data and Probability-Based constraints
Subject Areas : Journal of Value Chain ManagementYeganeh Malekmohammadi 1 , Javad Nematiyan 2
1 - Master's student in Industrial Engineering, Production and Service Systems, Tabriz University, Tabriz, Iran.
2 - Professor, Department of Industrial Engineering, Tabriz University, Tabriz, Iran.
Keywords: Fuzzy, Random, Single-row Facility Layout, Probability-based Constraint, Genetic Algorithm, Refrigeration Simulation Algorithm,
Abstract :
In this study, the single-row facility layout problem (SRFLP) is solved considering uncertainty in the flow data between facilities. Unlike classical models that consider the data as deterministic, in this study the flows are modeled as a combination of triangular fuzzy data and normal random variables. In order to transform the fuzzy-random model into a solvable form, the expected value method for fuzzy data and constrained chance programming (CCP) for the random part are used. The CCP constraint is defined such that the sum of the flows entering a critical facility with a given probability does not exceed a certain threshold. The final model is solved in two ways: exact solution using the LINGO software in finite dimensions, and genetic metaheuristic algorithms (GA) and simulated annealing (SA). The results showed that the proposed algorithms were able to produce feasible and less costly solutions than the exact solution. Also, comparison with the deterministic model without uncertainty showed that using the fuzzy-random model, while increasing realism, can also lead to better optimization in some situations. Finally, suggestions for developing the model in practical and theoretical dimensions are presented.
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