面向任务的最小最大MTSP蚁群算法

Li-Chih Lu, T. Yue
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引用次数: 33

摘要

多旅行推销员问题(MTSP)是一个组合优化问题,是著名的旅行推销员问题(TSP)的扩展。MTSP不仅具有学术研究价值,其应用也相当广泛。例如,车辆路由问题(VRP)和作业调度问题等,都可以简化为MTSP解决方案。MTSP是一个NP-Hard问题,值得从不同方面进行讨论来解决该问题。本研究采用蚁群优化算法(蚁群优化算法)。这种方法包含一定数量的任务协调蚁队,任务在蚁队中的蚂蚁出发前被指定(每只蚂蚁有不同的焦点搜索方向)。除了尝试完成自己的任务外,每只蚂蚁还将使用Max-Min哲学来协同工作以优化解决方案的质量。任务分配的目标是减少总距离,而路径的Max-Min搜索法的目标是达到Min-Max,这是劳动力平衡的目标。在求解过程中,每只蚂蚁会参考路径上的信息素浓度和任务提示作为它们的行动指南。每轮结束后,将根据从每个任务协调小组获得的解决方案状态改变任务配置,并重新配置路径上的信息素浓度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Mission-Oriented Ant-Team ACO for Min-Max MTSP
Multiple Traveling Salesman Problem (MTSP) is a combinatorial optimization problem and is an extension of the famous Traveling Salesman Problem (TSP). Not only does MTSP possess academic research value, its application is also quite extensive. For example, Vehicle Routing Problem (VRP) and Operations Scheduling, etc., can all be reduced to MTSP solutions. MTSP is an NP-Hard problem and is worth carrying out discussions from different facets to tackle the said problem. This research adopts the Ant Colony Optimization Algorithm (ACO). A certain amount of Mission-Coordinated Ant-Teams are included in this approach, and missions are appointed to the ants in the Ant-Teams before they set out (each ant has a different focal search direction). In addition to attempting to complete his or her own mission, each ant will use the Max-Min philosophy to work together to optimize the quality of the solution. The goal of the appointment of missions is to reduce the total distance, while the Max-Min search method for paths is to achieve Min-Max, which is the goal of labor balance. During the solving process, each ant will refer to the pheromone concentration on the paths and the mission tips as their action guidelines. After each round, the mission configuration will be changed in accordance with the state of solution obtained from each mission-coordinated team and the pheromone concentration on the path will be reconfigured.
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