摘要
针对物流配送系统中大规模车辆路径问题(VRP)很难在有限时间内得到最优解的问题,在分析了目前现有启发式算法的基础上,提出了采用遗传算法的解决方案,以及在交叉算子和变异算子中引出一个调整方法,使调整后的线路费用被进一步减少。该方法在一定程度上改进了遗传算法收敛速度慢的问题,并用VC++进行实现。最后两个实验结果表明,调整的遗传算法无论在运算时间还是运算结果上都是令人满意的,它可以有效地解决大规模的VRP问题。
Because the large-scaled vehicle route problem （VRP） of logistics distribution system is hard to get optimum solution in a limited period, a genetic method is adopted based on the analysis of the existing heuristic algorithm and an adjustment method which speeds the convergence of genetic algorithm is put forward and applied to crossover operator and mutation operator. The system is implemented with VC＋＋. Finally, the two experiments show that the adjusted genetic algorithm solve the large-scaled VRP validly and no matter the speed or the result are satisfied.
出处
《计算机工程与设计》
CSCD
北大核心
2009年第16期3783-3786,共4页
Computer Engineering and Design
基金
上海高校优秀青年教师科研专项基金项目(B-8101-06-3802)
关键词
物流配送系统
车辆路径问题(VRP)
遗传算法
优化
收敛
logistics distribution systems
vehicle route problem （VRP）
genetic algorithms
optimization
convergence
