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- W2034778582 abstract "This paper studies the scheduling problem of Hybrid Flow Shop (HFS) under the objective of minimizing makespan. The corresponding scheduling simulation system is developed in details, which employed a new encoding method so as to guarantee the validity of chromosomes and the convenience of calculation. The corresponding crossover and mutation operators are proposed for optimum sequencing. The simulation results show that the adaptive Genetic Algorithm (GA) is an effective and efficient method for solving HFS Problems." @default.
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- W2034778582 date "2013-08-01" @default.
- W2034778582 modified "2023-09-27" @default.
- W2034778582 title "Adaptive Genetic Algorithm for Hybrid Flow-Shop Scheduling" @default.
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- W2034778582 doi "https://doi.org/10.4028/www.scientific.net/amr.753-755.2925" @default.
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