A novel artificial immune system for solving multiobjective scheduling problems subject to special process constraint

• Published in: Computers & industrial engineering Vol. 58; no. 4; pp. 602 - 609
• Main Author: Gao, Jiaquan
• Format: Journal Article
• Language: English
• Published: New York Elsevier Ltd 01.05.2010; Pergamon Press Inc
• Subjects: Algorithms; Artificial immune system; Evolutionary algorithm; Genetic algorithms; Immune system; Job shops; Multiobjective scheduling; Parallel machines; Problem solving; Production scheduling; Simulation; Studies; Parallel machines; Evolutionary algorithm; Artificial immune system; Multiobjective scheduling
• ISSN: 0360-8352; 1879-0550
• DOI: 10.1016/j.cie.2009.12.009

This study presents a novel artificial immune system for solving a multiobjective scheduling problem on parallel machines (MOSP), which has the following characteristics: (1) parallel machines are nonidentical, (2) the type of jobs processed on each machine can be restricted, and (3) the multiobjective scheduling problem includes minimizing the maximum completion time among all the machines (makespan) and minimizing the total earliness/tardiness penalty of all the jobs. In this proposed algorithm, the cells are represented by a vector group, and a local search algorithm is incorporated to facilitate the exploitation of the search space. Specially, a new diversity technique is proposed to preserve the diversity of the population and enhance the exploration of the solution space. Simulation results show the proposed algorithm outperforms the vector immune genetic algorithm (VIGA).