基于节能环保的新视角,研究了以总油耗最小为目标的带时间窗车辆路径问题,建立了基于油耗的数学规划模型,提出了随机变邻域禁忌搜索算法。该算法选用自适应并行算法构造初始解,采用了随机变邻域搜索和重起策略。最后,对具有不同目标的带时间窗车辆路径问题进行了数值仿真,并对客户规模、等待期油耗率和时间窗的变化进行了性能分析。仿真结果表明,基于总油耗的路线安排比传统的以总运行距离或总运行时间最小为目标的路线安排具有更好的节油潜力,也更能减少对环境的污染。
From a new perspective of energy saving and environmental protection,a vehicle routing problem with time windows based on minimizing total fuel consumption was studied.Based on the minimum total fuel consumption,a mathmatical model was proposed.A novel tabu search algorithm with a Random Variable Neighborhood Descent procedure(RVND) was given,which used an adaptive parallel route construction heuristic,and employed a random neighborhood ordering and perturbation mechanisms.Finally,computational experiments were performed on vehicle routing problem with time windows based on different objective function.Performance analysis was conducted to study the effects of variance in number of clients,fuel consumption rate during waiting time,and time windows.The results show that the arrangement of minimizing total fuel consumption has the potential of yielding more savings in fuel consumption over the traditional arrangement of minimizing total travel distance or total travel time,and is better to reduce the pollution to the environment.