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首页> 外文期刊>Logistics >Heuristics Algorithms for a Heterogeneous Fleets VRP with Excessive Demand for the Vehicle at the Pickup Points, and the Longest Traveling Time Constraint: A Case Study in Prasitsuksa Songkloe, Ubonratchathani Thailand
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Heuristics Algorithms for a Heterogeneous Fleets VRP with Excessive Demand for the Vehicle at the Pickup Points, and the Longest Traveling Time Constraint: A Case Study in Prasitsuksa Songkloe, Ubonratchathani Thailand

机译：具有在接送点对车辆的过多需求和最长的行驶时间限制的异构机队VRP的启发式算法：以泰国乌汶市Prasitsuksa Songkloe为例

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摘要

This paper presents a methodology to solve a special case of the vehicle routing problem (VRP) called the heterogeneous fleets VRP with excessive demand of the vehicle at the pickup points, and the longest time constraint (HFVRP-EXDE-LTC). We developed two metaheuristics—a differential evolution (DE) algorithm and an adaptive large neighborhood search (ALNS)—to solve the problem. These two proposed methods have been designed to effectively solve a special case of VRP. From the computational results, we can see that the proposed heuristics outperformed the best practices that are currently in use. The DE yielded a 9.78% lower cost than that of the current practice (757,250 baht per year), while ALNS generated a 10.89% (906,750 baht per year) lower cost than that of current practice. Comparing the proposed heuristics, ALNS achieved a 1.01% lower cost than that of DE, as ALNS had a better mechanism that was designed to escape from the local optimal.
机译：本文提出了一种解决车辆路径选择问题（VRP）的特殊情况的方法，该问题称为异类车队VRP，在接载点车辆的需求过多，并且时间约束最长（HFVRP-EXDE-LTC）。为了解决该问题，我们开发了两种元启发式算法-差分进化（DE）算法和自适应大邻域搜索（ALNS）-。设计这两种建议的方法是为了有效解决VRP的特殊情况。从计算结果中，我们可以看到，所提出的启发式算法优于目前正在使用的最佳实践。 DE的成本比目前的实践降低了9.78％（每年757,250泰铢），而ALNS的成本比当前的实践降低了10.89％（每年906,750泰铢）。相比拟议的启发式方法，ALNS的成本比DE的成本低1.01％，因为ALNS具有更好的机制，可以摆脱局部最优。

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