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GECCO
2008
Springer
163views Optimization» more  GECCO 2008»
15 years 4 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»
15 years 6 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
15 years 9 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»
15 years 6 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»
15 years 4 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...