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Process Planning andScheduling inDistributedManufacturing SystemUsing MultiobjectiveGenetic Algorithm Wenqiang ZhangMitsuo Gen2009 год

Process Planning and Scheduling in Distributed Manufacturing System Using Multiobjective Genetic Algorithm
статья из журнала

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Аннотация: Abstract This paper proposed a multiobjective genetic algorithm approach for solving process planning and scheduling (PPS) problems in a distributed manufacturing system (DMS) environment. In this environment, factories processing various machines and tools at different geographical locations are often combined to produce various parts with different resource constraints. This paper proposed a fast multiobjective genetic algorithm with archive (fmoGA‐A) mechanism to deal with PPS problem with considering the minimization of the maximum total processing time and minimization of the maximum variation of workload of machine in DMS. The proposed algorithm has been compared with other approaches to testify and benchmark the optimization reliability on several PPS problems. These comparisons demonstrate the importance of PPS in DMS and indicate fmoGA‐A is better than adaptive weight approach genetic algorithm (awaGA) did on efficacy and efficient; the efficacy is not less than non‐dominated sorting genetic algorithm II (NSGA‐II) and strength Pareto evolutionary algorithm 2 (SPEA2) and the efficient is better than NSGA‐II and SPEA2. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.
Год издания: 2009
Авторы: Wenqiang Zhang, Mitsuo Gen
Издательство: Wiley
Источник: IEEJ Transactions on Electrical and Electronic Engineering
Ключевые слова: Scheduling and Optimization Algorithms, Advanced Manufacturing and Logistics Optimization, Advanced Control Systems Optimization