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A hybrid method to search the optimal Hamiltonian circuit

机译：一种搜索最佳Hamiltonian电路的混合方法

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摘要

The objective of the well-known travelling salesman problem (TSP) is to search the optimal Hamiltonian circuit (OHC) in a tourist map. Finding the OHC becomes hard once the number of the cities and routes in the tourist map are large. The four vertices and three lines inequality was introduced as the constraints of the local optimal Hamiltonian paths (LOHPs) included in the OHC. The chaotic depth-priority algorithm was designed by adding the computation process with the chaotic operator to verify the rationality of the LOHPs generated with the depth-priority algorithm under the inequality constraints. A lot of non-LOHPs are abandoned in the search process and the search space of the OHC is reduced greatly. The method was verified with an example and it can be applied to the network optimization, path planning, task scheduling, assembly sequence planning etc.
机译：众所周知的旅行推销员问题（TSP）的目的是在旅游地图中搜索最佳Hamiltonian电路（OHC）。一旦旅游地图中的城市和路线的数量大，就会发现OCC变得艰难。这四个顶点和三行不等式被引入了在OCC中包含的本地最佳Hamiltonian路径（LOHP）的约束。通过将计算过程添加与混沌操作员添加计算过程来设计混沌深度优先算法，以验证在不等式约束下用深度优先算法生成的LOHP的合理性。在搜索过程中放弃了许多非LOHP，并且OCC的搜索空间大大减少了。该方法用示例验证，它可以应用于网络优化，路径规划，任务调度，装配序列规划等。

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