Discrete imperialist competitive algorithm for the resource-constrained hybrid flowshop problem

Abstract

ABSTRACT The resource constrained scheduling problem has been investigated widely in recent years, and many heuristic algorithms have been applied to solve this problem. In this study, we propose a discrete imperialist competitive algorithm (DICA) to solve a variety of resource-constrained hybrid flowshop scheduling problems with the objective of minimizing the completion time. In the proposed algorithm, we employ a two-phase-based coding mechanism, where a local search method is applied. Then, we combine DICA and simulated annealing algorithm (SA) to improve the performance of the algorithm. In addition, we consider the dynamic allocation of resources in the decoding process. We tested the proposed algorithm based on a randomly generated set of real shop scheduling system instances, as well as numerically analyzing and comparing the proposed algorithm with existing heuristic algorithms to verify its effectiveness.