Differential evolutionary algorithms with novel mutation operator for solving the permutation flowshop scheduling problem

Abstract

Differential evolutionary (DE) algorithm is an effective algorithm to solve combinational optimization problems, such as scheduling problems. This paper aims to propose an improved differential evolutionary algorithm for the permutation flow-shop scheduling problem (PFSP) by considering the minimum makespan, where the new mutation mechanism is used to enable an appropriate sequencing for each job. For the reason, the main idea in this paper is to find out the key scheme from the better solution and making the assimilation operator in mutation procedure adopts the strategy based on the sequence. To evaluate the performance of the proposed approach, eight benchmark tests by Taillard's instance is used. The results demonstrate that the proposed improved differential evolutionary algorithm outperform than the conventional differential evolution algorithm.