Title: Green fuzzy parallel machine scheduling with sequence-dependent setup in the plastic moulding industry
Authors: Khodakaram Salimifard; Davood Mohammadi; Reza Moghdani; Abbas Abbasizad
Addresses: Computational Intelligence and Intelligent Optimization Research Group (CIIORG), Persian Gulf University, Bushehr 75168, Iran ' BFPIG, No. 123, Borazjan Road, Bushehr, Iran ' Computational Intelligence and Intelligent Optimization Research Group (CIIORG), Persian Gulf University, Bushehr 75168, Iran ' BFPIG, No. 123, Borazjan Road, Bushehr, Iran
Abstract: Job scheduling has always been a challenging task for production managers. It is of special importance if it involves multi-objectives and parallel machines. In this research, our direction is largely motivated by the uncertainty emerged in production systems, where processing times of jobs and setup times of machines are not fixed and they are subject to some uncertainties. Our paper presents a mixed-integer goal programming model considering fuzzy approach for parallel machines environments with separable jobs, sequence-dependent setup times and hazardous waste. Two fuzzy objectives are considered in the model to minimise the total tardiness and the total hazardous waste. Since the model is too complex to be solved using exact methods, we proposed a solution method based on genetic algorithm. To set the input parameters of the solution algorithm, Taguchi method is used. The results of the computational experiments indicate that the proposed algorithm is a proficient method and has efficiently found the optimal solutions for both objective functions.
Keywords: parallel machines; hazardous waste; genetic algorithms; fuzzy methods; meta-heuristics; scheduling.
Asian Journal of Management Science and Applications, 2019 Vol.4 No.1, pp.27 - 48
Received: 05 Feb 2019
Accepted: 31 Mar 2019
Published online: 07 Aug 2019 *