Total completion time minimization for scheduling of two-machine flow shop with deterioration jobs and setup time

Abstract

This article studies a scheduling problem of a two-machine flow shop with both time-dependent deteriorating jobs and sequence-independent setup time. It is assumed that the deterioration of processing time and setup time is of a linear increasing function with respect to the starting time. The objective is to minimize the total completion time of all jobs. For such a scheduling problem, a mixed integer programming model is developed to find an optimal solution for smallsized problems. For medium-and large-sized problems, a modified variable neighborhood search algorithm is presented. To improve the performance of the algorithm, a greedy algorithm is proposed to find a good initial solution. Also, lower bounds are presented for performance evaluation. Numerical experiments are used to evaluate the effectiveness and efficiency of the proposed method, and the results show that an optimal or near-optimal solution can be obtained.

Simulated Annealing Heuristic for Disposable Medical Face Mask Production Scheduling Problem

“…Bhongade and Khodke (2012) proposed two heuristics to deal with assembly flow shop scheduling problem where every part may not be processed on each machine. He et al (2017) presented a modified variable neighborhood search algorithm for two-machine flow shop scheduling problems with deterioration jobs and setup time. Zhou et al (2018) proposed a modified particle swarm optimization (MPSO) algorithm for the single batch-processing machine problem with non-identical job sizes and release times.…”