轮盘赌轮盘选择激励离散粒子群优化求解收费员调度问题

Pimolrat Ounsrimuang, S. Nootyaskool
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引用次数: 2

摘要

粒子群优化算法(PSO)在实际问题空间中的应用已经被证明可以解决各种各样的问题。在某些具体问题中,粒子群算法选择离散的问题空间,由于局部解黏滞导致求解速度较慢,而且研究人员无法修改或难以理解如何提高寻解性能。研究人员试图通过给新的c1, c2和权重一个更小或更大的值来调整速度值。本研究提出了如何应用轮盘选择来改进离散问题空间上的粒子群算法。实验通过一个收费员调度和一个数值函数验证了这一想法。这两个问题都创建了离散问题空间的参数。实验结果表明,采用轮盘选择的粒子群算法求解速度快。
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Roulette wheel selection to encourage discrete Particle Swarm Optimization solving toll-keeper scheduling problem
Particle Swarm Optimization (PSO) has been proven to solve various applications by most applications using the real problem-space. In some specific problem, the discrete problem-space is selected on PSO that getting the solution result slowly by cause of sticky on local solution, and also the researcher cannot modify or difficult to understand how to improve the performance finding solution. The researcher many be tried to adjust velocity value by giving a new c1, c2 and weight to be a smaller or a larger value. This research proposed how to apply roulette wheel select to improve PSO on the discrete problem-space. Experiment tested the idea by a toll-keeper scheduling and a numerical function. Both problems created parameters inform discrete problem-space. The experiment result showed that PSO with roulette wheel selection taking the solution quickly.
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