An Effective Artificial Bee Colony for Distributed Lot-Streaming Flowshop Scheduling Problem

Abstract

This paper proposes an effective discrete artificial bee colony (DABC) algorithm for solving the distributed lot-streaming flowshop scheduling problem (DLFSP) with the objective of minimizing makespan. We design a multi-list based representation to represent candidate solutions, where each list is corresponding to a factory. We present a multi-list based swap and insertion operators to generate neighboring solutions. We redesign the employ bee phase, onlooker bee phase, and scout bee phase according to the problem-specific knowledge, representation and information collected in the evolution process. The parameters for the proposed DABC algorithm are calibrated by means of a design of experiments and analysis of variance. A comprehensive computational campaign based on 810 randomly generated instances demonstrates the effectiveness of the proposed DABC algorithm for solving the DLFSP with the makespan criterion.