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GECCO
2006
Springer
145views Optimization» more  GECCO 2006»
14 years 2 days ago
Multi-objective test problems, linkages, and evolutionary methodologies
Existing test problems for multi-objective optimization are criticized for not having adequate linkages among variables. In most problems, the Pareto-optimal solutions correspond ...
Kalyanmoy Deb, Ankur Sinha, Saku Kukkonen
CEC
2007
IEEE
14 years 2 months ago
SAT-decoding in evolutionary algorithms for discrete constrained optimization problems
— For complex optimization problems, several population-based heuristics like Multi-Objective Evolutionary Algorithms have been developed. These algorithms are aiming to deliver ...
Martin Lukasiewycz, Michael Glaß, Christian ...
EMO
2009
Springer
190views Optimization» more  EMO 2009»
14 years 3 months ago
Solving Bilevel Multi-Objective Optimization Problems Using Evolutionary Algorithms
Abstract. Bilevel optimization problems require every feasible upperlevel solution to satisfy optimality of a lower-level optimization problem. These problems commonly appear in ma...
Kalyanmoy Deb, Ankur Sinha
GECCO
2007
Springer
300views Optimization» more  GECCO 2007»
14 years 2 months ago
Methodology to select solutions from the pareto-optimal set: a comparative study
The resolution of a Multi-Objective Optimization Problem (MOOP) does not end when the Pareto-optimal set is found. In real problems, a single solution must be selected. Ideally, t...
José C. Ferreira, Carlos M. Fonseca, Ant&oa...
GECCO
2007
Springer
185views Optimization» more  GECCO 2007»
14 years 2 months ago
SNDL-MOEA: stored non-domination level MOEA
There exist a number of high-performance Multi-Objective Evolutionary Algorithms (MOEAs) for solving MultiObjective Optimization (MOO) problems; two of the best are NSGA-II and -M...
Matt D. Johnson, Daniel R. Tauritz, Ralph W. Wilke...