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Approximate and exact algorithms for an energy minimization traveling salesman problem

机译:能量最小化旅行商问题的近似和精确算法

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Energy saving is a great challenge for clean transportation. In this paper, we study the Energy Minimization Traveling Salesman Problem (EMTSP), which is a generation of the classical Traveling Salesman Problem (TSP), and an important theoretical basis and a special case of the Energy Minimization Vehicle Routing Problem ( EMVRP). The objective of the studied problem is to minimize the sum of the product of load (including curb weight of the vehicle) and traveled distances. An approximation algorithm based on the Christofides's Heuristic is proposed and its worst-case ratio bound is proven. A branch and bound (B&B) algorithm integrated with a fast 1-tree based lower bound is developed to obtain optimal solutions. The results of computational experiments show the efficiency and the effectiveness of the B&B algorithm, as well as the heuristic methods. (C) 2019 Elsevier Ltd. All rights reserved.
机译:节能是清洁运输的巨大挑战。在本文中,我们研究了能量最小化旅行商问题(EMTSP),它是经典旅行商问题(TSP)的产生,并且是能量最小化车辆路线问题(EMVRP)的重要理论基础和特例。所研究问题的目的是最小化负载(包括车辆的整备质量)和行驶距离的乘积之和。提出了一种基于Christofides启发式算法的近似算法,并证明了其最坏情况下的比率边界。开发了与基于快速1树的下限集成的分支定界(B&B)算法,以获得最佳解决方案。计算实验结果表明了B&B算法的有效性和有效性以及启发式方法。 (C)2019 Elsevier Ltd.保留所有权利。

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