Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
An introduction to genetic algorithms
An introduction to genetic algorithms
An Introduction to Genetic Algorithms for Scientists and Engineers
An Introduction to Genetic Algorithms for Scientists and Engineers
Genetic Algorithms and Manufacturing Systems Design
Genetic Algorithms and Manufacturing Systems Design
Genetic Algorithms
Computers and Industrial Engineering
An adaptive genetic algorithm with dominated genes for distributed scheduling problems
Expert Systems with Applications: An International Journal
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In dealing with the production of various products in some industries, many firms need to respond to wide ranges of quantities demanded. High responsiveness to wider ranges of quantities can be a competitive advantage for a firm in modern highly competing environments. To stay ahead of competitors, a firm should be able to schedule production in an efficient way. The purpose of this study is to investigate the effects of wide ranges of quantities demanded on the scheduling. The production scheduling problem of knitted fabrics is used to examine the influences. Genetic algorithm (GA) is employed to be the analytical tool. Optimal parameters including mutation rates and crossover rates that generate good performance are obtained experimentally. Results from this paper show that the makespan in wide ranges of quantities is lower than that in a small range. However, the machine utilization in wide ranges of quantities is lower than that in a small range. To schedule the production with a lower makespan and with reasonable machine utilization, one can divide a big customer order into many manufacturing orders with smaller quantities. In addition, the on-time delivery rate can be increased by adding a penalty factor of completion time of a job.