文章摘要
张异.包装废弃物回收车辆路径问题的改进遗传算法[J].包装工程,2018,39(17):147-152.
ZHANG Yi.Improved Genetic Algorithm for Vehicle Routing Problem in Packaging Waste Recycling[J].Packaging Engineering,2018,39(17):147-152.
包装废弃物回收车辆路径问题的改进遗传算法
Improved Genetic Algorithm for Vehicle Routing Problem in Packaging Waste Recycling
投稿时间:2018-05-24  修订日期:2018-09-10
DOI:10.19554/j.cnki.1001-3563.2018.17.024
中文关键词: 包装废弃物  回收  车辆路径问题  遗传算法
英文关键词: packaging waste  recycling  vehicle routing problem  genetic algorithm
基金项目:重庆市教委人文社科项目(16SKGH209);重庆工商职业学院重点项目(ZD2014-03)
作者单位
张异 重庆工商职业学院重庆 401520 
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中文摘要:
      目的 采用优化传统遗传算法(GA)研究包装废弃物回收车辆路径问题(VRP)的性能。方法 提出改进遗传算法(IGA)。首先,设计基于贪婪算法的初始种群生成算子,提高初始种群质量;其次,设计根据适应度值大小、进化代数等自适应调整的交叉和变异概率;然后,设计最大保留交叉算子,保证种群的多样性;最后,对企业实例和标准算例进行仿真测试。结果 采用IGA算法、蚁群算法(ACO)能求得算例最优解,且IGA算法运行速度快于ACO算法,分支界定算法(BBM)、传统GA算法无法求得算例最优解。结论 与BBM算法、传统GA算法和ACO算法相比,IGA算法求解包装废弃物回收VRP问题的整体性能更优。
英文摘要:
      The work aims to optimize the performance of traditional genetic algorithm (GA) used to solve the vehicle routing problem (VRP) in packaging waste recycling. An improved genetic algorithm (IGA) was put forward. Firstly, in order to improve the quality of initial population, the initial population generation operator based on greedy algorithm was designed; secondly, the crossover and mutation probabilities adaptively adjusted based on fitness values and evolutionary algebras were designed; then, the maximum preserved crossover operator was designed to ensure population diversity. Finally, simulation tests were carried out on an enterprise instance and standard examples. IGA and ant colony algorithm (ACO) were used to get the optimal solution of the example, and IGA ran faster than ACO. The branch and bound algorithm (BBM) and traditional GA could not find the optimal solution of the example. Compared with the BBM, traditional GA and ACO, IGA has better overall performance in solving the VRP problem of packaging waste recycling.
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