On the use of informed initialization and extreme solutions sub-population in multiobjective evolutionary algorithms

2009 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, MCDM 2009 - Proceedings

Volumn , Issue , 2009, Pages 58-65

  Dasgupta, Dipankar ^a   Hernandezy, German ^b   Romeroy, Andres ^b   Garrett, Deon ^a   Kaushal, Aishwarya ^a   Simienz, James ^c  

^a University of Memphis   (United States)

^b UNIVERSIDAD NACIONAL DE COLOMBIA   (Colombia)

^c Studies   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BENCH-MARK PROBLEMS; BEST APPROXIMATIONS; EXTREME POINTS; INITIAL POPULATION; INITIAL SOLUTION; INTERNAL POINTS; LOCAL SEARCH ALGORITHM; MULTI OBJECTIVE EVOLUTIONARY ALGORITHMS; PARETO FRONT; SELECTION SCHEME; SINGLE OBJECTIVE; WEIGHT VECTOR;

APPROXIMATION ALGORITHMS; ARTIFICIAL INTELLIGENCE; DECISION MAKING; LEARNING ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION; PARETO PRINCIPLE;

EVOLUTIONARY ALGORITHMS;

EID: 67650563491     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/MCDM.2009.4938829     Document Type: Conference Paper

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