计算机应用与软件Issue(10)：291-293,314,4.DOI:10.3969/j.issn.1000-386x.2015.10.069
基于改进多目标遗传算法求解混合流水车间调度问题
SOLVING HYBRID FLOW-SHOP SCHEDULING BASED ON IMPROVED MULTI-OBJECTIVE GENETIC ALGORITHM
张志鹏 1黄明1
作者信息
- 1. 大连交通大学软件学院 辽宁 大连 116028
- 折叠
摘要
Abstract
Based on the advantages of multi-objective genetic algorithm and particle swarm optimisation,we proposed a multi-objective hy-brid algorithm for solving hybrid flow-shop scheduling problem (HFSP).It introduces an extended process-based encoding,takes the optimal solutions of these two algorithms as the initial factor for each other,and speeds up the evolution of genetic algorithm as well as avoids PSO falling into local optimum,thus realises the flexible scheduling of production workshops with different processing routes.Finally,through nu-merical simulation of example we verified the effectiveness of the algorithm.关键词
混合流水车间调度/遗传算法/粒子群算法/多目标优化Key words
Hybrid flow-shop scheduling/Genetic algorithm/Particle swarm optimisation/Multi-objective optimisation分类
信息技术与安全科学引用本文复制引用
张志鹏,黄明..基于改进多目标遗传算法求解混合流水车间调度问题[J].计算机应用与软件,2015,(10):291-293,314,4.
