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Optimization of Traveling Salesman Problem with Precedence Constraint using Particle Swarm Optimizationud

机译:使用粒子群算法优化具有优先约束的旅行商问题 ud

摘要

Traveling salesman problem with precedence constraint (TSPPC) is one of the complex problems in combinatorial optimization. Many researchers have suggested various mechanisms to solve this problem effectively. This work presents a combination of Particle Swarm Optimization (PSO) and Topological Sort approach to optimize TSPPC. The original PSO is designed for continuous problem. Therefore, it is incapable to optimize TSPPC, besidesudthe reason of precedence constraint. The proposed PSO with Topological Sort approach was tested with differentudsize of TSPPC problem. The optimization result showed that it yielded better performance in finding the shortest travelling time in all problem size. This finding is associated with better exploration and solution diversity features in PSO.
机译:具有优先约束的旅行商问题(TSPPC)是组合优化中的复杂问题之一。许多研究人员提出了各种机制来有效解决此问题。这项工作提出了粒子群优化(PSO)和拓扑排序方法的组合,以优化TSPPC。原始的PSO是为连续问题而设计的。因此,除了优先约束的原因外,还无法优化TSPPC。提出的带有拓扑排序方法的PSO在不同大小的TSPPC问题上进行了测试。优化结果表明,在所有问题大小中找到最短的旅行时间时,它具有更好的性能。这一发现与PSO中更好的探索和解决方案多样性功能相关。

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