文章摘要
路径优化问题的遗传算法研究与实现
Research on Genetic Algorithm and Implementation in Routing Optimization
  
DOI:
中文关键词: 车辆路径问题;遗传算法;适应度;交叉;变异
英文关键词: Vehicle routing problems; genetic algorithm; fitness; crossover; variation
基金项目:
作者单位
吕树红  
江豪  
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中文摘要:
      论文针对多种约束条件下的车辆路径问题,提出一种改进的遗传算法。该算法的目标是解决在不同车型、装载率、最大行驶距离等条件下的配送车辆路径优化和调度问题。该算法首先对多条件下的车辆路径问题构建数学模型,用于评价解的适应度;然后经过“生成初始种群、更改操作算子、调整选择和变异概率”等策略对传统遗传算法模型进行再设计。结果表明,改进后的新算法对多条件下的车辆路径问题具有更好的最优解和更可靠的全局稳定性。
英文摘要:
      This paper proposes an improved genetic algorithm to address the vehicle routing problem under multiple constraints. The objective of the algorithm is to solve the routing optimization and delivery vehicle scheduling problems under the conditions of different models of vehicles, loading rate and maximum driving distance. Firstly, a mathematical model is constructed concerning the vehicle routing problem under the multiple conditions to evaluate the fitness of the solution, and then the traditional genetic algorithm model is re designed by the adoption of the strategies such as “generating the initial population, changing the operator, adjusting the selection and mutation probability”. The simulated experiment results show that the new algorithm has a better optimal solution and a more reliable global stability towards the multi conditional vehicle routing problems.
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