An Artificial Bee Colony Algorithm for the Distributed Hybrid Flowshop Scheduling Problem

Abstract

Abstract The distributed hybrid flowshop scheduling problem (DHFSP) is derived from the hybrid flowshop scheduling problem (HFSP), which involves two scheduling assignment decisions—assignment of jobs to factories and scheduling jobs in each factory. DHFSP is encountered in many practical industry applications recently. The standard DHFSP has never been discussed in any previous literature, and it is addressed first addressed in this work. In this paper, the mixed-integer linear programming (MILP) model is proposed. An improved discrete artificial bee colony (DABC) algorithm for minimizing makespan is proposed as well. Novel encoding and decoding methods are developed for DHFSP. The constructive heuristic, an improved NEH heuristic, is employed to build high quality and diversified solutions for the initial population. Two neighborhood search methods based on swap and insertion neighborhood structures are proposed for DHFSP. Comprehensive computational comparisons and statistical analysis demonstrate the effectiveness of the proposed DABC algorithm when compared with a genetic algorithm (GA) and an iterated greedy (IG) algorithm.