Iterated Local Search Based Heuristic for Scheduling Jobs on Unrelated Parallel Machines with Machine Deterioration Effect

Abstract

In this research, we study an unrelated parallel machine scheduling problem in which the jobs cause deterioration of the machines. This deterioration decreases the performance of the machines, therefore the processing times of the jobs are increased over time. The problem is to find the processing sequence of jobs on each machine in order to reduce the deterioration of the machines and consequently minimize the makespan. Given that the problem is NP-hard, we propose an Iterated Local Search (ILS) heuristic to obtain near-optimal solutions. In this work we combine ILS meta-heuristic with Random Variable Neighborhood Descent (RVND) local search. The performance of our heuristic is compared with the state-of-the-art meta-heuristic algorithm proposed in the literature for the problem under study. The results show that the our heuristic outperform the existing algorithm by a significant margin.