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GECCO
2008
Springer
163views Optimization» more  GECCO 2008»
13 years 8 months ago
Embedded evolutionary multi-objective optimization for worst case robustness
In Multi-Objective Problems (MOPs) involving uncertainty, each solution might be associated with a cluster of performances in the objective space depending on the possible scenari...
Gideon Avigad, Jürgen Branke
GECCO
2006
Springer
179views Optimization» more  GECCO 2006»
13 years 11 months ago
Comparison of multi-objective evolutionary algorithms in optimizing combinations of reinsurance contracts
Our paper concerns optimal combinations of different types of reinsurance contracts. We introduce a novel approach based on the Mean-Variance-Criterion to solve this task. Two sta...
Ingo Oesterreicher, Andreas Mitschele, Frank Schlo...
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 ...
GECCO
2006
Springer
134views Optimization» more  GECCO 2006»
13 years 11 months ago
Reference point based multi-objective optimization using evolutionary algorithms
: Evolutionary multi-objective optimization (EMO) methodologies have been amply applied to find a representative set of Pareto-optimal solutions in the past decade and beyond. Alth...
Kalyanmoy Deb, J. Sundar
GECCO
2008
Springer
132views Optimization» more  GECCO 2008»
13 years 8 months ago
Hybridizing an evolutionary algorithm with mathematical programming techniques for multi-objective optimization
In recent years, the development of multi-objective evolutionary algorithms (MOEAs) hybridized with mathematical programming techniques has significantly increased. However, most...
Saúl Zapotecas Martínez, Carlos A. C...