64 Ahybrid Differential Evolution Algorithm with Variable Neighborhood Search for a Bi-Objective Parallel Machine Scheduling Problem

In this paper, we propose a novel two-phase hybrid differential evolution (DE) algorithm with a variable neighborhood search method in order to enhance the exploitation ability of the algorithm. The algorithm is developed to solve a new NP-hard bi-objective parallel machine scheduling problem with earliness-tardiness and workload balancing as two objective functions. Due to the priority of the former, this paper attempts to apply a hierarchical approach for DE. Because of the discrete nature of scheduling problems, a random-key solution representation is used to encode solutions. The solutions provided by the proposed algorithm for 200 test problems with various sizes, outperform one of the state-of-the-art evolutionary algorithm, the two-phase genetic algorithm.