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An Efficient Two-Objective Hybrid Local Search Algorithm for Solving the Fuel Consumption Vehicle Routing Problem

机译:解决油耗车辆路径问题的高效两目标混合局部搜索算法

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The classical model of vehicle routing problem (VRP) generally minimizes either the total vehicle travelling distance or the total number of dispatched vehicles. Due to the increased importance of environmental sustainability, one variant of VRPs that minimizes the total vehicle fuel consumption has gained much attention. The resulting fuel consumption VRP (FCVRP) becomes increasingly important yet difficult. We present a mixed integer programming model for the FCVRP, and fuel consumption is measured through the degree of road gradient. Complexity analysis of FCVRP is presented through analogy with the capacitated VRP. To tackle the FCVRP's computational intractability, we propose an efficient two-objective hybrid local search algorithm (TOHLS). TOHLS is based on a hybrid local search algorithm (HLS) that is also used to solve FCVRP. Based on the Golden CVRP benchmarks, 60 FCVRP instances are generated and tested. Finally, the computational results show that the proposed TOHLS significantly outperforms the HLS.
机译:车辆路径问题(VRP)的经典模型通常使总的车辆行驶距离或调度的车辆总数最小化。由于环境可持续性的重要性日益提高,一种最小化车辆总油耗的VRP变体已引起了广泛关注。最终的燃油消耗量VRP(FCVRP)变得越来越重要,但也越来越困难。我们提出了FCVRP的混合整数规划模型,并且通过道路坡度来测量油耗。 FCVRP的复杂性分析是通过与功能强大的VRP进行类比来进行的。为了解决FCVRP的计算难点,我们提出了一种高效的两目标混合本地搜索算法(TOHLS)。 TOHLS基于混合本地搜索算法(HLS),该算法也用于解决FCVRP。根据Golden CVRP基准,生成并测试了60个FCVRP实例。最后,计算结果表明,提出的TOHLS明显优于HLS。

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    College of Economics and Management, Shandong University of Science and Technology, Qingdao 266590, China;

    School of Management Science and Engineering, Dongbei University of Finance and Economics, Dalian 116025, China;

    Department of Marketing, Transportation and Supply Chain, School of Business and Economics, North Carolina A & T State University, Greensboro, NC 27411, USA;

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