摘要
车辆路径问题是一个典型的组合优化类问题,遗传算法是求解此类问题的方法之一。针对遗传算法容易出现"早熟"现象的问题,借鉴免疫算法通过抗体浓度抑制以保持种群多样性的优势以及模拟退火算法的个体选择策略,提出了一种改进的遗传算法,并将其用于解决车辆路径问题。实验验证了算法的有效性以及求解的效率和解的质量。
Vehicle routing problem is a typical combinational optimization problem.Genetic algorithm is one of the methods used to solve VRP.Aiming at the defects of premature convergence in the evolution process of genetic algorithmt,his thesis designs an improved genetic algorithmr,eferring the advantages of immune algorithm which uses antibody concentration re-striction to keep population diversity and the individual choice approach of simulated annealing algorithm.The improved ge-netic algorithm is used to solve VRP in the thesis.Some experiment data prove the effectiveness of the algorithm and authen-ticate the search efficiency and solution quality of the algorithm.
出处
《计算机工程与应用》
CSCD
北大核心
2010年第36期219-221,共3页
Computer Engineering and Applications
基金
国家自然科学基金(No.60842004)
中南民族大学校基金项目(No.YZQ07016)~~
关键词
遗传算法
车辆路径问题
组合优化
genetic algorithm
vehicle routing problem
combinational optimization
