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Discrete novel hybrid particle swarm optimization to solve travelling salesman problem

机译:离散新型混合粒子群算法求解旅行商问题

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Metaheuristics is a set of intelligent nature inspired method, it aims to solve some optimization problems, such as quadratic assignment problem, knapsack problem, and graph colouring problem. Resolving an optimization problem consist in applying a mathematic process to find the minimum or the maximum solution depending on the constraints of the problem. In this paper, the travelling salesman problem is chosen to test the performance of a new proposed discrete novel hybrid particle swarm optimization. This method presents a combination between particle swarm optimization and harmony search algorithm, where harmony search improved the swarm. An experimental result of a different methaheuristics shows the efficiency of the proposed method for solving some benchmarks instances of TSPLib.
机译:元启发法是一组智能的自然启发方法,旨在解决一些优化问题,例如二次分配问题,背包问题和图着色问题。解决优化问题的方法是应用数学过程,根据问题的约束条件找到最小或最大解决方案。在本文中,选择旅行商问题来测试新提出的离散新型混合粒子群优化算法的性能。该方法提出了粒子群优化与和声搜索算法的结合,其中和声搜索改善了群体。不同的方法论的实验结果表明,该方法解决了TSPLib的一些基准实例的效率。

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