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首页> 外文期刊>Journal of computer sciences >OPTIMIZING MULTIPLE TRAVELLING SALESMAN PROBLEM CONSIDERING THE ROAD CAPACITY
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OPTIMIZING MULTIPLE TRAVELLING SALESMAN PROBLEM CONSIDERING THE ROAD CAPACITY

机译:考虑道路通行能力的多个旅行推销员问题的优化

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摘要

The Multiple Travelling Salesman Problems (MTSP) can be used in a wide range of discrete optimization problems. As the solution to this problem has wide applicability in many practical fields, this NP Hard problem highly raises the need for an efficient solution. The problem is determining a set of routes for the salesmen that jointly visit a set of given cities which are facing difficulty because of road congestion. Selection of proper route is based on the road capacity, which is the deciding factor in the opt vehicle usage. The objective of the study is to optimize the vehicle utilization and minimize the time of travel by salesman based on the road capacity. The solution to this problem is achieved in 3 steps; the first step is by assigning addresses to cities by Ad-assignment algorithm. The second step is by assigning cities and vehicles to salesman by Sl-assignment algorithm. The third step is by using Parallel Shortest Path Multiple Salesman (PSPMS) algorithms to obtain the shortest path. The PSPMS algorithm runs in parallel for each salesman. The solutions to the problem are known to possess an exponential time complexity. From the result we observe that PSPMS is one of the best approximate algorithms used to solve MTSP.
机译:多重旅行商问题(MTSP)可用于各种离散的优化问题。由于该问题的解决方案在许多实际领域中具有广泛的适用性,因此该NP Hard问题极大地提出了对有效解决方案的需求。问题是为推销员确定一组路线,这些推销员共同访问由于道路拥堵而面临困难的给定城市。选择适当的路线取决于道路通行能力,这是选择使用车辆的决定性因素。该研究的目的是基于道路通行能力来优化车辆利用率,并最大程度地减少推销员的出行时间。这个问题的解决方案可以通过3个步骤实现:第一步是通过广告分配算法为城市分配地址。第二步是通过S1分配算法将城市和车辆分配给推销员。第三步是使用并行最短路径多个销售员(PSPMS)算法来获得最短路径。 PSPMS算法对每个推销员并行运行。已知该问题的解决方案具有指数时间复杂度。从结果可以看出,PSPMS是用于解决MTSP的最佳近似算法之一。

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