標題: A multiobjective hybrid genetic algorithm for the capacitated multipoint network design problem
作者: Lo, CC
Chang, WH
資訊管理與財務金融系 註:原資管所+財金所
Department of Information Management and Finance
關鍵字: genetic algorithms;minimal spanning tree;multiobjective function;nondominated solution;subpopulation
公開日期: 1-六月-2000
摘要: The capacitated multipoint network design problem (CMNDP) is NP-complete, In this paper, a hybrid genetic algorithm for CMNDP is proposed. The multiobjective hybrid genetic algorithm (MOHGA) differs from other genetic algorithms (GA's) mainly in its selection procedure. The concept of subpopulation is used in MOHGA, Four subpopulations are generated according to the elitism reservation strategy, the shifting Prufer vector, the stochastic universal sampling, and the complete random method, respectively, Mixing these four subpopulations produces the next generation population. The MOHGA can effectively search the feasible solution space due to population diversity, The MOHGA has been applied to CMNDP. By examining computational and analytical results, we notice that the MOHGA can find most nondominated solutions and is much more effective and efficient than other multiobjective GA's.
URI: http://dx.doi.org/10.1109/3477.846234
http://hdl.handle.net/11536/30487
ISSN: 1083-4419
DOI: 10.1109/3477.846234
期刊: IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS PART B-CYBERNETICS
Volume: 30
Issue: 3
起始頁: 461
結束頁: 470
顯示於類別:期刊論文


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  1. 000087662600007.pdf