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Extension of PSO and ACO-PSO algorithms for solving Quadratic Assignment Problems

机译:PSO和ACO-PSO算法扩展,用于解决二次分配问题

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In this paper,PSO and Ant Colony Optimization inspired PSO (ACO-PSO) algorithms were adopted to solve the Quadratic Assignment Problems.A hybrid approach is adopted in this paper by combining assignment construction with local-search.In the PSO algorithm,solution construction has been carried out by assigning weights to current,particle’s best and global best solutions associated with assignment of resources.Velocities which are used to construct the assignments in this approach are similar to the trail intensities considered in the ant colony algorithms.The proposed algorithms have been applied to a set of benchmark problems and the performance of the algorithm is evaluated by testing the obtained results with the results published in the literature.The computational results show that good quality solutions are obtained using the PSO and ACO inspired PSO algorithm.
机译:在本文中,采用PSO和蚁群优化启发了PSO(ACO-PSO)算法来解决二次分配问题。通过将分配结构与本地研究组合,解决方案构建,解决了这些论文中采用了混合方法。已经通过将权重分配给当前的权重,粒子的最佳和全球最佳解决方案与资源分配相关联。用于构建这种方法中的作业的差异,类似于蚁群算法中考虑的路径强度。该算法具有已应用于一组基准问题,并通过在文献中发布的结果测试所获得的结果来评估算法的性能。计算结果表明,使用PSO和ACO启发PSO算法获得了良好的质量解决方案。

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