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An Improved Heuristic For The Capacitated Arc Routing Problem

机译:电容弧布线问题的一种改进的启发式方法

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The capacitated arc routing problem (CARP) is an important and practical problem in the OR literature. In short, the problem is to identify routes to service (e.g., pickup or deliver) demand located along the edges of a network such that the total cost of the routes is minimized. In general, a single route cannot satisfy the entire demand due to capacity constraints on the vehicles. CARP belongs to the set of NP-hard problems; consequently numerous heuristic and metaheuristic solution approaches have been developed to solve it. In this paper an "ellipse rule" based heuristic is proposed for the CARP. This approach is based on the path-scanning heuristic, one of the mostly used greedy-add heuristics for this problem. The innovation consists basically of selecting edges only inside ellipses when the vehicle is near the end of each route. This new approach was implemented and tested on three standard datasets and the solutions are compared against: (i) the original path-scanning heuristic; (ii) two other path-scanning heuristics and (iii) the three best known metaheuristics. The results indicate that the "ellipse rule" approach lead to improvements over the three path-scanning heuristics, reducing the average distance to the lower bound in the test problems by about 44%.
机译:电容电弧路由问题(CARP)是OR文献中的一个重要而实际的问题。简而言之,问题在于识别沿网络边缘定位的服务(例如,提货或交付)需求的路由,从而使路由的总成本最小化。通常,由于车辆的容量限制,单条路线不能满足全部需求。 CARP属于NP难题集合。因此,已经开发了许多启发式和元启发式解决方案来解决它。在本文中,针对CARP提出了一种基于“椭圆规则”的启发式算法。这种方法基于路径扫描启发式算法,该算法是此问题最常用的贪婪添加启发式算法之一。该创新基本上包括在车辆接近每条路线的尽头时仅在椭圆内选择边。该新方法已在三个标准数据集上实施和测试,并将解决方案与以下各项进行了比较:(i)原始路径扫描启发式算法; (ii)其他两种路径扫描启发式方法,以及(iii)三种最著名的元启发式方法。结果表明,“椭圆规则”方法导致对三种路径扫描启发式方法的改进,使到测试问题下限的平均距离减少了约44%。

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