Hybridization Simulated Annealing Algorithm in a Single Machine Scheduling Problem

Abstract

In this paper, we investigate a single machine scheduling problem (SMSP). We try to reach the optimal or near optimal solution which minimize the sum of three objective functions: total completion times, total tardiness and total earliness. Firstly, we solve this problem by Branch and bound algorithm (BAB alg) to find optimal solutions, dominance rules (DR)s are used to improve the performance of BAB alg, the resulting is BABDR, secondly, we solve this problem by simulated annealing algorithm (SA alg) as metaheuristic algorithm (MET alg). It is known that combining MET alg with other algorithms can improve the resulting solutions. In this paper we developed the concept of insertion preselected jobs one by one through all positions of remaining jobs of considered sequence, the proposed MET alg called Insertion Metaheuristic Algorithm (IMA). This procedure improves the performance of SA alg in two directions: in the first one, we use the IMA to generate initial solution for SA alg, in the second one, we use the IMA to improve the solution obtained through the iterations of SA alg. The experiments showed that IMA can improve the performance of SA alg in these two directions.