Title: Flowshop sequence-dependent group scheduling with minimisation of weighted earliness and tardiness
Authors: Taha Keshavarz; Nasser Salmasi; Mohsen Varmazyar
Addresses: Department of Industrial Engineering, Yazd University, P.O. Box 89195-741, Yazd, Iran ' Corning Incorporated, 310 N College RD, Wilmington, NC, 28405, USA ' Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran
Abstract: In this research, we approach the flowshop sequence-dependent group scheduling problem with minimisation of total weighted earliness and tardiness as the objective for the first time. A mixed integer linear programming model is developed to solve the problem optimally. Since the proposed research problem is proven to be NP-hard, a hybrid meta-heuristic algorithm based on the particle swarm optimisation (PSO) algorithm, enhanced with neighbourhood search is developed to heuristically solve the problem. Since the objective is a non-regular, a timing algorithm is developed to find the best schedule for each sequence provided by the metaheuristic algorithm. A lower bounding method is also developed by reformulating the problem as a Dantzig-Wolf decomposition model to evaluate the performance of the proposed PSO algorithm. The computational results, based on using available test problems in the literature, demonstrate that the proposed PSO algorithm and the lower bounding method are quite effective, especially in the instances with loose due date. [Received: 17 February 2018; Revised: 27 July 2018; Accepted: 25 August 2018]
Keywords: earliness; tardiness; sequence-dependent setup time; group scheduling; Dantzig-Wolf decomposition; particle swarm optimisation; PSO.
European Journal of Industrial Engineering, 2019 Vol.13 No.1, pp.54 - 80
Available online: 21 Feb 2019 *Full-text access for editors Access for subscribers Purchase this article Comment on this article