A Coevolution Genetic Programming Method to Evolve Scheduling Policies for Dynamic Multi-objective Job Shop Scheduling Problems

Created by W.Langdon from gp-bibliography.bib Revision:1.7615

@InProceedings{Nguyen:2012:CECb,

• title = "A Coevolution Genetic Programming Method to Evolve Scheduling Policies for Dynamic Multi-objective Job Shop Scheduling Problems",
• author = "Su Nguyen and Mengjie Zhang and Mark Johnston and Tan Kay Chen",
• pages = "3332--3339",
• booktitle = "Proceedings of the 2012 IEEE Congress on Evolutionary Computation",
• year = "2012",
• editor = "Xiaodong Li",
• month = "10-15 " # jun,
• DOI = "doi:10.1109/CEC.2012.6252968",
• address = "Brisbane, Australia",
• ISBN = "0-7803-8515-2",
• keywords = "genetic algorithms, genetic programming, Heuristics, metaheuristics and hyper-heuristics, Evolutionary simulation-based optimization",
• abstract = "A scheduling policy (SP) strongly influences the performance of a manufacturing system. However, the design of an effective SP is complicated and time-consuming due to the complexity of each scheduling decision as well as the interactions between these decisions. This paper proposes novel multi-objective genetic programming based hyper-heuristic methods for automatic design of SPs including dispatching rules (DRs) and due-date assignment rules (DDARs) in job shop environments. The experimental results show that the evolved Pareto front contains effective SPs that can dominate various SPs from combinations of existing DRs with dynamic and regression-based DDARs. The evolved SPs also show promising performance on unseen simulation scenarios with different shop settings. On the other hand, the proposed Diversified Multi-Objective Cooperative Coevolution (DMOCC) method can effectively evolve Pareto fronts of SPs compared to NSGA-II and SPEA2 while the uniformity of SPs obtained by DMOCC is better that those evolved by NSGA-II and SPEA2.",
• notes = "WCCI 2012. CEC 2012 - A joint meeting of the IEEE, the EPS and the IET.",

}

Genetic Programming entries for Su Nguyen Mengjie Zhang Mark Johnston Kay Chen Tan

Citations