Solving an Extended Multi-Row Facility Layout Problem With Fuzzy Clearances Using GA

Applied Soft Computing, 2017

Posted: 25 Mar 2020

See all articles by Soroush Safarzadeh

Soroush Safarzadeh

Isfahan University of Technology

Hamidreza Koosha

Mashhad Ferdowsi University, Mashhad, Iran

Date Written: 2017

Abstract

Multi-row facility layout problem (MRFLP) is a class of facility layout problems, which decides upon the arrangement of facilities in some fixed numbers of rows in order to minimize material handling cost. Nowadays, according to the new layout requirements, the facility layout problems (FLPs) have many applications such as hospital layout, construction site layout planning and layout of logistics facilities. Therefore, we study an extended MRFLP, as a novel layout problem, with the following main assumptions: 1) the facilities are arranged in a two-dimensional area and without splitter rows, 2) multiple products are available, 3) distance between each pair of facilities, due to inaccurate and flexible manufacturing processes and other limitations (such as WIPs, industrial instruments, transportation lines and etc.), is considered as fuzzy number, and 4) the objective function is considered as minimizing the material handling and lost opportunity costs. To model these assumptions, a nonlinear mixed-integer programming model with fuzzy constraints is presented and then converted to a linear mixed-integer programming model. Since the developed model is an NP-hard problem, a genetic algorithm approach is suggested to find the best solutions with a minimum cost function. Additionally, three different crossover methods are compared in the proposed genetic algorithm and finally, a sensitivity analysis is performed to discuss important parameter.

Keywords: Facility Layout, Multi-Row Facility Layout Problem (MRFLP), Genetic Algorithm, Lost Opportunity Cost, Fuzzy Sets

Suggested Citation

Safarzadeh, Soroush and Koosha, Hamidreza, Solving an Extended Multi-Row Facility Layout Problem With Fuzzy Clearances Using GA (2017). Applied Soft Computing, 2017, Available at SSRN: https://ssrn.com/abstract=3546431

Soroush Safarzadeh (Contact Author)

Isfahan University of Technology ( email )

Khomeyni Shahr, Daneshgah e Sanati HW
Isfahan
Iran

Hamidreza Koosha

Mashhad Ferdowsi University, Mashhad, Iran ( email )

Here is the Coronavirus
related research on SSRN

Paper statistics

Abstract Views
48
PlumX Metrics