An evolutionary many-objective optimization algorithm based on dominance and decomposition

IEEE Transactions on Evolutionary Computation

Volumn 19, Issue 5, 2015, Pages 694-716

  Li, Ke ^a   Deb, Kalyanmoy ^a   Zhang, Qingfu ^b,c   Kwong, Sam ^b  

^a Michigan State University   (United States)

^b CITY UNIVERSITY OF HONG KONG   (Hong Kong)

^c UNIVERSITY OF ESSEX   (United Kingdom)

Author keywords

constrained optimization; decomposition; evolutionary computation; Many objective optimization; Pareto optimality; steady state

Indexed keywords

BENCHMARKING; DECOMPOSITION; EVOLUTIONARY ALGORITHMS; MULTIOBJECTIVE OPTIMIZATION; PARETO PRINCIPLE; PROBLEM SOLVING;

COMPETITIVE PERFORMANCE; CONSTRAINED OPTIMI-ZATION PROBLEMS; EVOLUTIONARY MULTIOBJECTIVE OPTIMIZATION; EVOLUTIONARY PROCESS; MANY-OBJECTIVE OPTIMIZATIONS; PARETO-OPTIMALITY; STATE-OF-THE-ART ALGORITHMS; STEADY STATE;

CONSTRAINED OPTIMIZATION;

EID: 84959346507     PISSN: 1089778X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TEVC.2014.2373386     Document Type: Article

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