Optimization of operation sequencing based on feasible operation sequence oriented genetic algorithm

被引：0
|
作者：
Dou J. [1 ]
Li J. [2 ]
Su C. [1 ]
机构：
[1] School of Mechanical Engineering, Southeast University, Nanjing
[2] School of Automation, Southeast University, Nanjing
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2019年 / 25卷 / 08期
关键词：
Feasible operation sequence; Genetic algorithms; Operation sequencing; Process planning;
D O I：
10.13196/j.cims.2019.08.012
中图分类号：
学科分类号：
摘要：
To solve the operation sequencing problem in CAPP that is a NP-hard problem, a new Feasible Operation Sequence Oriented Genetic Algorithm (FOSOGA) was developed to minimize the total cost. In the FOSOGA, a Feasible Operation Sequence (FOS) satisfying the precedence constraints was encoded by a permutation. The crossover with adaptive crossover probability and the mutation with adaptive mutation probability were designed to evolve FOS and relevant machining resources recorded in any chromosome and keep the feasibility of the chromosomes. In addition, a new elitist-based crossover mechanism was introduced in the FOSOGA. The proposed FOSOGA was applied to two industrial cases and was compared with existing Genetic Algorithm (GA), ant colony optimization (ACO) and particle swarm optimization (PSO). The comparative results showed that FOSOGA was superior than existing GA, ACO and PSO for average solution quality. © 2019, Editorial Department of CIMS. All right reserved.
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页码：1981 / 1990
页数：9
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