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Discrete Particle Swarm Optimization with Chaotic Initialization

机译:Chaotic Initialization的离散粒子群优化

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A discrete particle swarm algorithm with chaotic initialization (DPSO-CI) is proposed for solving the combinational optimization problems, such as knapsack. The presented algorithm mainly employs the chaotic idea and pheromone mechanism used by ant colony algorithm. There are two reasons for using the ideas. To start with, the information existing in populations can be fully shared. Further, the initial solutions will not be gathered due to using chaotic method. At a matter of fact, swarm information can be more sufficiently shared by each particle. The performance of the proposed algorithm is evaluated in comparison with other heuristic algorithms. Our computational simulations reveal very encouraging results in terms of the quality of solution found.
机译:提出了一种具有混沌初始化(DPSO-CI)的离散粒子群算法,用于解决组合优化问题,例如背包。呈现的算法主要采用蚁群算法使用的混沌思想和信息素机制。使用思想有两个原因。首先,可以完全共享群体中存在的信息。此外,由于使用混沌方法,不会收集初始解决方案。事实上,每个粒子可以更充分地共享群体信息。与其他启发式算法相比,评估了所提出的算法的性能。我们的计算模拟在发现的解决方案质量方面揭示了非常令人鼓舞的结果。

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