勤益科大機構典藏:Item 987654321/6689
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    Please use this identifier to cite or link to this item: http://ir.lib.ncut.edu.tw/handle/987654321/6689


    Title: A Modified Particle Swarm Optimization Algorithm with Cases Studies
    Authors: 陳鴻誠
    Contributors: 電機工程(學)系
    Date: 2011-07
    Issue Date: 2017-11-23 09:21:33 (UTC+8)
    Abstract: s paper presents a hybrid algorithm, the “particle swarm optimization with simulated annealing behavior (SA-PSO)” algorithm, which combines the advantages of good solution quality in simulated annealing and fast calculation in particle swarm optimization. As stochastic optimization algorithms are sensitive to its parameters, this paper introduces criteria in selecting parameters to improve solution quality. To prove the usability and effectiveness of the proposed algorithm, simulations are performed using 20 different mathematical optimized functions of different dimensions. The results made from different algorithms are then compared between the quality of the solution, the efficiency of searching for the solution and the convergence characteristics. According to the simulation results, SA-PSO obtained higher efficiency, better quality and faster convergence speed than other compared algorithms.
    Relation: Advanced Materials Research
    Appears in Collections:[Department of Electrical Engineering] 【電機工程系所】期刊論文

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