标题： 何时在解决CVRP时使用模拟退火？ 波兰燃料配送案例研究 显示英文标题

标题： When to use simulated annealing for solving CVRP? A case study of fuel deliveries in Poland

摘要： 本文研究了在向加油站供应燃料的背景下有容量限制的车辆路径问题（CVRP）。 CVRP的目标是使具有有限容量的车队总行驶距离最小化。 然而，燃料配送在CVRP框架内引入了独特的复杂性。 我们提出了一种新颖的方法，将模拟退火（SA）算法与专门针对加油站网络设计的定制CVRP模型相结合。 该模型结合了现实世界中的约束条件，如车辆容量、每个加油站的燃料需求以及道路网络的距离。 本文概述了基于SA的CVRP模型在燃料配送中的设计。 我们详细描述了目标函数（最小化距离）以及SA的探索机制，用于生成候选解决方案。 为了评估其有效性，所提出的方案在由Samat运输公司服务的波兰加油站网络中进行了计算测试。 我们将基于SA的CVRP模型性能与由Gurobi驱动的传统混合整数规划模型在CVRP中的性能进行了比较。 结果旨在展示基于SA的启发式方法在寻找高效燃料配送路线方面的有效性。 显示英文摘要

摘要： The paper addresses Capacitated Vehicle Routing Problem (CVRP) in the context of fuel delivery to gas stations. The CVRP aims to minimize total travel distance for a fleet with limited capacity. Fuel delivery, however, introduces unique complexities within the CVRP framework. We propose a novel approach that integrates the Simulated Annealing (SA) algorithm with a customized CVRP model specifically designed for gas station networks. This model incorporates real-world constraints like vehicle capacity, fuel demands at each station, and road network distances. The paper outlines the design of SA-based CVRP model for fuel delivery. We detail the objective function (minimizing distance) and the SA's exploration mechanism for generating candidate solutions. To assess its effectiveness, the proposed approach undergoes computational tests in Poland's gas station network serviced by the Samat transportation company. We compare the performance of our SA-based CVRP model with the conventional Mixed Integer Programming model for CVRP powered by Gurobi. The results aim to demonstrate the efficacy of the proposed SA-based heuristic in finding efficient routes for fuel deliveries.