摘要
为克服车辆调度优化存在容易陷入局部解问题,提出了一种改进的模拟退火遗传算法。该算法在遗传算法的交叉和变异概率、变异个体的选取等环节引入了模拟退火机制,实现了模拟退火和遗传算法的融合,改善了遗传算法的搜索能力、搜索效率和收敛性能。计算结果验证了算法的有效性和正确性。
To solve the local local optimal solution problem of vehicle scheduling problem,a simulated annealing genetic algorithm is put forward in this paper. The algorithm combines simulated annealing algorithm with genetic algorithm in choosing of crossover and mutation probability as well as mutation individual to further improve its searching space,searching efficiency and convergence performance. Calculation results show that the algorithm proposed in the paper is valid and correct.
出处
《微计算机信息》
2010年第31期232-233,179,共3页
Control & Automation
关键词
车辆调度问题
遗传算法
模拟退火算法
早熟收敛
Vehicle Scheduling Problem
Genetic Algorithm
Simulated Annealing Algorithm
Premature Convergence
