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GECCO
2005
Springer
131views Optimization» more  GECCO 2005»
10 years 5 months ago
Multipopulation cooperative coevolutionary programming (MCCP) to enhance design innovation
This paper describes the development of an evolutionary algorithm called Multipopulation Cooperative Coevolutionary Programming (MCCP) that extends Genetic Programming (GP) to sea...
Emily M. Zechman, S. Ranji Ranjithan
GECCO
2005
Springer
124views Optimization» more  GECCO 2005»
10 years 5 months ago
Generalized benchmark generation for dynamic combinatorial problems
Several general purpose benchmark generators are now available in the literature. They are convenient tools in dynamic continuous optimization as they can produce test instances w...
Abdulnasser Younes, Paul H. Calamai, Otman A. Basi...
GECCO
2005
Springer
219views Optimization» more  GECCO 2005»
10 years 5 months ago
An evolutionary lagrangian method for the 0/1 multiple knapsack problem
We propose a new evolutionary approach to solve the 0/1 multiple knapsack problem. We approach the problem from a new viewpoint different from traditional methods. The most remar...
Yourim Yoon, Yong-Hyuk Kim, Byung Ro Moon
GECCO
2005
Springer
10 years 5 months ago
Flight midcourse guidance control based on genetic algorithm
Zhao-hua Yang, Jian-cheng Fang, Zhen-qiang Qi
GECCO
2005
Springer
101views Optimization» more  GECCO 2005»
10 years 5 months ago
Evolving agents for network centric warfare
Ang Yang, Hussein A. Abbass, Ruhul A. Sarker
GECCO
2005
Springer
163views Optimization» more  GECCO 2005»
10 years 5 months ago
Memory-based immigrants for genetic algorithms in dynamic environments
Investigating and enhancing the performance of genetic algorithms in dynamic environments have attracted a growing interest from the community of genetic algorithms in recent year...
Shengxiang Yang
GECCO
2005
Springer
150views Optimization» more  GECCO 2005»
10 years 5 months ago
Population-based incremental learning with memory scheme for changing environments
In recent years there has been a growing interest in studying evolutionary algorithms for dynamic optimization problems due to its importance in real world applications. Several a...
Shengxiang Yang
GECCO
2005
Springer
10 years 5 months ago
Probabilistic distribution models for EDA-based GP
This paper proposes a novel technique for a program evolution based on probabilistic models. In the proposed method, two probabilistic distribution models with probabilistic depen...
Kohsuke Yanai, Hitoshi Iba
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