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A green vehicle routing problem with time windows considering the heterogeneous fleet of vehicles: two metaheuristic algorithms

机译:考虑到超均匀车队的时间窗口的绿色车辆路由问题:两个成群质算法

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摘要

In this paper, the green vehicle routing problem with time windows constraint is studied in the presence of a heterogeneous fleet of vehicles and filling stations. In addition, the number of vehicles and their fuel tank capacity are both limited. The main contribution of this study is the simultaneous consideration of these features, which makes the problem more practical. For this purpose, a mixed integer linear programming model that minimises the transportation costs and (or carbon dioxide) emissions, is proposed. Furthermore, a genetic algorithm and a population-based simulated annealing are developed to find high-quality solutions for large-scale instances. To validate the proposed model and algorithms, 28 instances are generated using a benchmark database. The computational results demonstrate that both algorithms provide efficient solutions regarding the objective function value and CPU time. Finally, a comprehensive sensitivity analysis is carried out to show the importance of features mentioned above.
机译:本文在车辆和填充站的异构队列存在下,研究了时间窗限制的绿色车辆路由问题。此外,车辆的数量及其燃料箱容量均为有限。本研究的主要贡献是同时考虑这些功能,这使得更实用的问题。为此目的,提出了一种最大限度地减少运输成本和(或二氧化碳)排放的混合整数线性编程模型。此外,开发了一种遗传算法和基于群体的模拟退火,以找到大型实例的高质量解决方案。为了验证所提出的模型和算法,使用基准数据库生成28个实例。计算结果表明,这两种算法都为目标函数值和CPU时间提供有效的解决方案。最后,进行了全面的敏感性分析,以显示上述功能的重要性。

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