A Hybrid Harmony Search and Simulated Annealing Algorithm for Job Shop Scheduling Problem

Abstract

This paper proposes a novel approach to address the Job Shop Scheduling Problem (JSSP) by combining the Harmony Search (HS) and Simulated Annealing (SA) algorithm. The proposed method employs the SA algorithm to generate initial solutions and new solutions for the HS algorithm. By exploring a wide range of solutions including worse ones, SA can effectively navigate the complex search space and generate diverse solutions for HS to optimize. This results in enhanced global search abilities and improved convergence of the HS algorithm for JSSP. Experimental results demonstrate the efficiency and efficacy of the proposed approach in solving JSSP.