Journal
EXPERT SYSTEMS WITH APPLICATIONS
Volume 39, Issue 11, Pages 10016-10021Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2012.01.211
Keywords
Flexible job shop; Scheduling; Parallel machine; Genetic Algorithm; Grouping Genetic Algorithm; Makespan; Tardiness
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Funding
- National Science Council (NSC) of Taiwan, ROC
- Chung-Shan Institute of Science and Technology of Taiwan, ROC [NSC 94-2623-7-033-003]
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Based on Genetic Algorithm (GA) and Grouping Genetic Algorithm (GGA), this research develops a scheduling algorithm for job shop scheduling problem with parallel machines and reentrant process. This algorithm consists of two major modules: machine selection module (MSM) and operation scheduling module (OSM). MSM helps an operation to select one of the parallel machines to process it. OSM is then used to arrange the sequences of all operations assigned to each machine. A real weapon production factory is used as a case study to evaluate the performance of the proposed algorithm. Due to the high penalty of late delivery in military orders and high cost of equipment investment, total tardiness, total machine idle time and makespan are important performance measures used in this study. Based on the design of experiments, the parameters setting for GA and GGA are identified. Simulation results demonstrate that MSM and OSM respectively using GGA and GA outperform current methods used in practice. (c) 2012 Elsevier Ltd. All rights reserved.
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