Integration of process planning and scheduling based on immune genetic algorithm

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8 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)1807-1813
Journal / PublicationJisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS
Volume12
Issue number11
Publication statusPublished - Nov 2006
Externally publishedYes

Abstract

To realize the concurrent distributed integration of process planning and scheduling, a mathematical model of simulating optimization of process and scheduling was established. The decision space, objective functions, and constraints of the model were defined. A co-evolutionary immune genetic algorithm was proposed to simultaneously optimize the combination of alternative process and production scheduling. Collaborative evolution was realized through the interaction between process population and scheduling population, the affinity and concentration of antibody were used to guarantee the diversity of population, the stimulation of antibody was used to realize immune selection, and the elitism keeping strategy was used to guarantee the convergence of the algorithm. To deal with the characteristics of codes, the uniform crossover and random disturbance mutation were used for the process antibody, whereas the uniform order crossover and reverse mutation were used for the scheduling antibody. Simulation of 10 machines and 10 parts was performed to illustrate the validity of the algorithm.

Research Area(s)

  • Concentration of antibody, Immune genetic algorithm, Immune selection, Optimization of process and scheduling, Stimulation of antibody

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