关于整车物流运输车辆路径优化设计的研究

Study on Vehicle Routing Problems in Logistics Distribution

为了使整车物流运输路程最短,费用最少以及提高物流配送中心轿运车的利用率,设计最优的车辆物流装载方案和运输计划,构建车辆路径优化模型;针对传统智能算法在求解该问题时收敛性弱、易陷入局部极值点的不足,提出贪心算法和遗传算法相结合的混合算法进行仿真求其最优解。其次,通过采取交叉、变异算子的自适应控制策略以改善算法的全局搜索能力。仿真结果表明:贪心算法可以改进装载方案,遗传算法可以提供运输策略,二者结合的混合算法在收敛代数以及求解性能上均有较大改进,可为车辆路径优化设计供有效解决方案。

For the purpose of reducing transportation consumption of the logistics vehicle routing optimization and improving Car- carrier＇s utilization, we established a vehicle routing optimization model by designing an optimal loading scheme of vehicle logistics and transportation plan. First, a hybrid genetic algorithm was presented for overcoming the defects in tradition intelligent optimization algorithm, the low solving efficiency and falling into the local con- vergence. Second, an adaptive control strategy of crossover and mutation parameters was introduced to improve the a- bility of global search, and a local search based on crossover and mutation operator was adopted in the hybrid genetic algorithm. The simulation results demonstrate that the greedy algorithm can improve the loading scheme, the genetic algorithm can provide transportation strategy, the mixed genetic algorithm behaves better in convergence algebra and solving performance, and can provide effective plan in solving the optimal vehicle routing problem.