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GECCO
2008
Springer
132views Optimization» more  GECCO 2008»
13 years 5 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...
GECCO
2005
Springer
120views Optimization» more  GECCO 2005»
13 years 10 months ago
Exploiting gradient information in numerical multi--objective evolutionary optimization
Various multi–objective evolutionary algorithms (MOEAs) have obtained promising results on various numerical multi– objective optimization problems. The combination with gradi...
Peter A. N. Bosman, Edwin D. de Jong
CEC
2009
IEEE
13 years 11 months ago
Local search based evolutionary multi-objective optimization algorithm for constrained and unconstrained problems
Abstract— Evolutionary multi-objective optimization algorithms are commonly used to obtain a set of non-dominated solutions for over a decade. Recently, a lot of emphasis have be...
Karthik Sindhya, Ankur Sinha, Kalyanmoy Deb, Kaisa...
GECCO
2007
Springer
194views Optimization» more  GECCO 2007»
13 years 11 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational techniq...
Rui Li, Bir Bhanu, Krzysztof Krawiec
EVOW
2007
Springer
13 years 11 months ago
Tackling the Container Loading Problem: A Hybrid Approach Based on Integer Linear Programming and Genetic Algorithms
Abstract. This paper presents a novel hybrid approach for solving the Container Loading (CL) problem based on the combination of Integer Linear Programming (ILP) and Genetic Algori...
Napoleão Nepomuceno, Plácido Rog&eac...