A discrete estimation of distribution particle swarm optimization for combinatorial optimization problems

被引：0
作者：
Zhou, Yalan [1 ]
Wang, Jiahai
Yin, Han [1 ]
机构：
[1] Sun Yat Sen Univ, Dept Comp Sci, 135 Xingang W Rd, Guangzhou 510275, Peoples R China
来源：
ICNC 2007: THIRD INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION, VOL 4, PROCEEDINGS | 2007年
基金：
中国国家自然科学基金;
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The philosophy behind the original particle swarm optimization (PSO) is to learn from individual's own experience and the best individual experience in the whole swarm. Estimation of distribution algorithms (EDAs) generate new solutions from a probability model which characterizes the distribution of promising solutions in the search space at each generation. In this paper, a discrete estimation of distribution particle swarm optimization algorithm (DEDPSO) is proposed for combinatorial optimization problems. The proposed algorithm combines the statistical information collected from the local best solutions information of all individuals and the global best solution information found so far in the whole swarm. The results show that the proposed algorithm has superior performance to other discrete PSOs.
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页码：80 / +
页数：2
相关论文
共 16 条
  • [1] [Anonymous], P IEEE C SYST MAN CY, DOI DOI 10.1109/ICSMC.1997.637339
  • [2] [Anonymous], GENETIC ALGORITHMS E
  • [3] [Anonymous], S AFRICAN COMPUTER J
  • [4] Baluja S., 1994, CMUCS94163
  • [5] El-Gallad AI, 2001, ENG INTELL SYST ELEC, V9, P155
  • [6] The compact genetic algorithm
    Harik, GR
    Lobo, FG
    Goldberg, DE
    [J]. IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 1999, 3 (04) : 287 - 297
  • [7] Karp R. M., 1972, COMPLEXITY COMPUTER, P85, DOI DOI 10.1007/978-1-4684-2001-2_9
  • [8] Kennedy J, 1995, 1995 IEEE INTERNATIONAL CONFERENCE ON NEURAL NETWORKS PROCEEDINGS, VOLS 1-6, P1942, DOI 10.1109/icnn.1995.488968
  • [9] Learning probability distributions in continuous evolutionary algorithms - A comparative review
    Kern S.
    Müller S.D.
    Hansen N.
    Büche D.
    Ocenasek J.
    Koumoutsakos P.
    [J]. Natural Computing, 2004, 3 (1) : 77 - 112
  • [10] The Equation for Response to Selection and Its Use for Prediction
    Muehlenbein, Heinz
    [J]. EVOLUTIONARY COMPUTATION, 1997, 5 (03) : 303 - 346
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