摘要
作业调度问题(JSP)是一类典型的NP-hard问题,遗传算法作为一种通用的优化算法在求解JSP中得到了广泛的应用。本文主要针对作业车间调度问题,基于改进的遗传算法,根据种群的进化状况,从而确定种群的适应度值,使之能够保持种群的多样化。
The job-shop scheduling problem （JSSP） is one of the most difficult combinatorial optimization problems, and it is also a typical NP-hard problem. GA（Genetie Algorithm）, as a current optimized algorithm, has been used widely for JSP. In order to solve the problem of job-shop scheduling, and according to the condition of population evolution, this paper presents a new adaptive algorithm with a new crossover and mutation method based on the improved genetic algorithm, and realizes a multi-population crossover in order to keep the population＇s diversification.
出处
《计算机工程与科学》
CSCD
2008年第10期48-50,共3页
Computer Engineering & Science
关键词
作业车间调度
遗传算法
自适应遗传算法
job-shop scheduling
genetic algorithm
adaptive genetic algorithm
