2005
DOI: 10.1016/j.cie.2004.07.007
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A genetic algorithm with sub-indexed partitioning genes and its application to production scheduling of parallel machines

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Cited by 33 publications
(12 citation statements)
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“…Genetic algorithms are commonly used to solve parallel machine scheduling problems (e.g., by Mendes et al, 2002;Jou, 2005;Vallada & Ruiz, 2011). In each iteration, which is also referred to as a generation, a genetic algorithm maintains a population of several solutions and tries to reach better solutions by stylized application of evolutionary principles.…”
Section: Hybrid Genetic Algorithmmentioning
confidence: 99%
“…Genetic algorithms are commonly used to solve parallel machine scheduling problems (e.g., by Mendes et al, 2002;Jou, 2005;Vallada & Ruiz, 2011). In each iteration, which is also referred to as a generation, a genetic algorithm maintains a population of several solutions and tries to reach better solutions by stylized application of evolutionary principles.…”
Section: Hybrid Genetic Algorithmmentioning
confidence: 99%
“…In the proposed algorithm, such parents are selected using the roulette wheel method. The roulette wheel selection method ranks the chromosomes based on their fitness function values and then assigns them a probability distribution that favors good chromosomes, so as to obtain a better chance of producing good next generations [17]. It has the following steps [11]:…”
Section: Reproductionmentioning
confidence: 99%
“…Also, the bits of the searched parameters will be large if high precision is desired. Therefore, real-parameter GA was proposed and applied to versatile problems such as mechanism design (Ha et al, 2005(Ha et al, , 2006, scheduling system (Jou, 2005;Ruiz and Maroto, 2006), and control system (Arumugam et al, 2005;Wang et al, 2005). However, some inherent shortcomings of GA, e.g.…”
Section: Introductionmentioning
confidence: 99%