Adaptive Genetic Algorithm for Hybrid Flow-Shop Scheduling

Xiao Chun Zhu; Jian Feng Zhao; Mu Lan Wang

doi:10.4028/www.scientific.net/AMR.753-755.2925

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Determination of Occurrence Grades for Factors Affecting Congelation Failure on Basis of Fuzzy Comprehensive Assessment Method
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Adaptive Genetic Algorithm for Hybrid Flow-Shop Scheduling
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The Properties of Solutions on a Class of Parabolic System
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 753-755Adaptive Genetic Algorithm for Hybrid Flow-Shop...

Adaptive Genetic Algorithm for Hybrid Flow-Shop Scheduling

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.