摘要
针对遗传算法在解决车辆路径问题时效率较低的缺点,将寿命和年龄的概念引入遗传算法,提出了多代竞争遗传算法。每次通过遗传或变异更新一定数量的个体,对于个体按其年龄和寿命决定其是否留在下一代种群中,或终止其生命。通过这种方式,增加了较优秀个体在种群中的存活时间,加大了其繁殖几率和优秀基因被子代个体继承的概率。并应用算法对实际算例进行了测算,取得较满意结果。多代竞争遗传算法对其他优化问题同样适用。
Age and life- span is introduced to genetic algorithms for overcoming the low efficiency, which is used to VRP. The multi - generation compete genetic algorithms is put forward. At each iteration, some individuals are updated by descendiblity and variation. Each individual, according to its age and life - span, is judged whether it is kept down to next generation population, or its life tO be terminated. By this means, saved generations of some better individuals are prolonged in the generation population, and the probability of their propagatation and better - gene genetic increased. In the end, some better numerical solutions are presented through using the algorithms. Multi - Generation GA can also be used to solute the other optimal problems.
出处
《铁道科学与工程学报》
CAS
CSCD
北大核心
2005年第5期75-79,共5页
Journal of Railway Science and Engineering
关键词
物流配送
车辆路径
多代竞争
遗传算法
logistics distribution
vehicle routing problem
multi- generation compete
genetic algorithms
