Multi-Objective Variable Neighborhood Search Algorithms

Abstract

The Multi-Objective Single Machine Scheduling (MOSMS) Problem is one of the most representative problems in the scheduling area. In this paper, we compare five multi-objective algorithms based on Variable Neighborhood Search (VNS) heuristic. The algorithms are applied to solve the MOSMS problem. In this problem, we consider minimizing the total completion times and minimizing the sum of maximum earliness/tardiness. We introduce two intensification procedures to improve a Multi-Objective Variable Neighborhood Search (MOVNS) algorithms proposed in the literature. The performance of the algorithms is tested on a set of instances of the problem. The computational results show that the proposed algorithms outperform the original MOVNS algorithms in terms of efficiency solutions.