An effective genetic algorithm for the flexible job-shop scheduling problem

Expert Systems with Applications

Volumn 38, Issue 4, 2011, Pages 3563-3573

  Zhang, Guohui ^a   Gao, Liang ^b   Shi, Yang ^b  

^a ZHENGZHOU INSTITUTE OF AERONAUTICAL INDUSTRY MANAGEMENT   (China)

^b HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

Author keywords

Chromosome representation; Flexible job shop scheduling; Genetic algorithm; Initialization

Indexed keywords

BENCHMARK DATA; COMPUTATIONAL RESULTS; CROSSOVER AND MUTATION; FLEXIBLE JOB-SHOP SCHEDULING; FLEXIBLE JOB-SHOP SCHEDULING PROBLEM; HIGH QUALITY; INITIAL POPULATION; INITIALIZATION; INITIALIZATION STAGE; MAKESPAN;

CHROMOSOMES; COMPUTATIONAL EFFICIENCY; GENETIC ALGORITHMS; MATHEMATICAL OPERATORS;

SCHEDULING ALGORITHMS;

EID: 78650682362     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2010.08.145     Document Type: Article

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