A comparative study of metaheuristics for parallel-machine job shop scheduling: A case study of scancom

Abstract

This abstract presents a comparative study of solving the Parallel Machine Job Shop Scheduling Problem (JSSP), applied in the case of a wood manufacturing company in Vietnam, using three different optimization techniques: CPLEX, Simulated Annealing (SA), and Tabu Search (TS). The objective is to minimize the makespan, i.e., the total time required to complete all jobs on multiple machines simultaneously. Benchmark instances from the literature are utilized to evaluate the solution quality and computational efficiency of each method. CPLEX consistently provides optimal or near-optimal solutions but exhibits limitations in scalability. SA and Tabu Search offer good-quality solutions with reasonable computational times, making them viable alternatives for large-scale JSSP instances. Some comparison is conducted to assess the robustness of each method to different problem parameters. This study provides insights into the performance and effectiveness of these optimization techniques, aiding in the selection of the most appropriate method for solving the Parallel Machine JSSP. After the comparison between MILP, TS and SA, an implementation would be applied for the larger data set.