An Improved Discrete Artificial Bee Colony Algorithm for Distributed Permutation Flowshop Scheduling Problem with Sequence Dependent Setup Times

Abstract

The distributed permutation flowshop scheduling problem (DPFSP) has attracted much attention in recent years due to the increasing benefits of multi-factory manufacture. However, DPFSP with sequence-dependent setup times, a very relevant and meaningful problem for today’s dynamic manufacturing environment, has not captured much attention so far. This paper investigates DPFSP with sequence-dependent setup times (SDST) under minimization of total flowtime. Base on the special characteristics of this problem, this paper presents an improved discrete artificial bee colony (IDABC) algorithm to obtain high-quality solutions in reasonable CPU times. The framework of IDABC adopts an effective variable neighborhood search algorithm with two stage local search, and an acceleration mechanism based on neighborhood swap operator. Compared with DABC, the experimental results gives a better performance for solving the DPFSP with total flowtime criterion.