摘要
针对资源选择提出了一种以最小的竞标花费和交通运费为优化目标的算法,该算法分两步完成。首先,通过对时间因素的排除,将0-1整数规划问题转化成2次指派问题;其次,在引入虚拟资源和虚拟任务之后,提出了一种基于遗传算法的优化算法。通过引入虚拟资源或虚拟任务,使得该算法种群的编码、初始化,以及交叉算子的设计等都变得非常简单,从而大大提高了运算速度。最后的实例分析也表明了该算法的有效性。
It posed a resource selection algorithm basing on the minimum cost which included bidding cost and transporting cost, and the was turned into two steps. First, we turned a quadratic programming problem into QAP（quadratic assignment problem） by crossing out the factor of time; then, it posed the GA after bringing into the virtual resources or virtual tasks. It made the crossover, mutation and selection of genctic algorithm easily, and also the running speed became faster. Finally, an example was analyzed to demonstrate the effectiveness of the method.
出处
《机械设计与制造》
北大核心
2007年第5期129-131,共3页
Machinery Design & Manufacture
关键词
资源选择
遗传算法
虚拟资源
Resource selection
Genetic algorithm
Virtual resources
