An efficient self-adaptive artificial bee colony algorithm for the distributed resource-constrained hybrid flowshop problem

Abstract

Distributed factory processing has attracted the attention and application of many companies because of the low cost and high flexibility. In the present study, the self-adaptive artificial bee colony algorithm (SABC) is presented to solve the distributed resource-constrained hybrid flowshop scheduling (DRCHFS) problems aiming to minimize the makespan. In the proposed algorithm, the two-dimensional vector solution representation is employed. Then, resource constraint in the decoding process is considered. In addition, a self-adaptive perturbation structure and local search strategy based on the critical factory are investigated to enhance searching abilities. The proposed algorithm is tested based on a randomly generated set of the real shop scheduling system, and then numerically analyze and compare the proposed algorithm with the existing heuristic algorithms to verify its effectiveness.