Title: Metaheuristic algorithms for the generalised cell formation problem considering machine reliability
Authors: Mohammad Mahdi Nasiri; Foruzan Naseri
Addresses: School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran; Department of Industrial Engineering, Alzahra University, Tehran, Iran ' School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran; Department of Industrial Engineering, Alzahra University, Tehran, Iran
Abstract: In this paper, we use two metaheuristic algorithms, i.e., artificial bee colony (ABC) and covariance matrix adaptation revolution strategies (CMA-ES), for solving the generalised cell formation problem considering machine reliability. The purpose is to choose the best process routing for each part and to allocate the machines to the manufacturing cells in order to minimise the total cost, which is composed of intracellular movement cost, intercellular movement cost and machines breakdown cost. To evaluate the metaheuristic algorithms, eight numerical examples in three different sizes are solved. The results of the two algorithms are compared with each other and with the results of solving the MIP model. Both the MIP solver and metaheuristics find the optimal solutions for the small size problem instances while by increasing the problem size, metaheuristics show higher performance. The results illustrate that the CMA-ES algorithm outperforms the ABC algorithm in both solution quality and CPU time.
Keywords: group technology; generalised cell formation problem; reliability; artificial bee colony; ABC; covariance matrix adaptation revolution strategies; CMA-ES.
International Journal of Process Management and Benchmarking, 2019 Vol.9 No.4, pp.469 - 484
Accepted: 09 Oct 2017
Published online: 04 Nov 2019 *