Modern Manufacturing Engineering ›› 2017, Vol. 442 ›› Issue (7): 114-120.doi: 10.16731/j.cnki.1671-3133.2017.07.023

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Research on material distribution multi-objective optimization model based on improved genetic algorithm

Chen Guangsheng, Dong Baoli   

  1. Faculty of Mechanical Engineering & Automation,Zhejiang Sci-Tech University,Hangzhou 310018,China
  • Received:2016-05-13 Online:2017-07-18 Published:2017-09-29

Abstract: To solve the problem of various material distribution routes and uncertain operators in assembly shop,considering the utilization of operators and the loading rate of material vehicle,an optimization model of lean material distribution was proposed with the target of minimizing total distribution time and the number of operators.The improved genetic algorithm was used to solve this model.In order to solve the problem that the multi-objective optimization genetic algorithm difficult to converge in practice and have a lot of illegal solution,in the design process of algorithm,it uses integer coding to reflect directly operators distribution routing and allocation of tasks,and add illegal solutions for inspection in crossover and mutation.The example verifies feasibility and effectiveness of optimization model.

Key words: assembly shop, material distribution, the number of operators, improved genetic algorithm

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