摘要
针对多目标柔性作业车间调度问题,提出一种改进遗传算法。该算法为了克服传统遗传算法的局限性,提高全局搜索能力和收敛性,采用一种新的GOR编码、新的分类选择算子和改进的优先操作交叉算子集成设计方法,定义编码的种群平均个体差,其交叉率和变异率受种群的多样性控制。通过典型算例的实验及与国内外最新的研究成果比较,证明了算法的优良性能。
An Improved Genetic Algorithm （GA） was presented for solving the flexible job shop scheduling problem（FJSP） with multi-object. In this algorithm, a new encoding Grannt chart Oriented Representation（GOR）, new selection operator Sort,new crossover operator Improved Precedence Operation crossover （IPOX） were designed, and the rates of crossover and mutation were controlled by population multiformity, in order to overcome the limitations of traditional GA. The feasibility and validity of the proposed algorithm have been proved by the results obtained from the computational study and the comparison with others.
出处
《中国机械工程》
EI
CAS
CSCD
北大核心
2007年第2期156-160,共5页
China Mechanical Engineering
基金
国家自然科学基金资助重大项目(59990470)
关键词
柔性作业车间调度
遗传算法
多目标优化
自适应
flexible job shop scheduling
genetic algorithm
multi- object optimization
self-adaptive
