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ICNC
2009
Springer
14 years 2 months ago
An Improved Greedy Genetic Algorithm for Solving Travelling Salesman Problem
—Genetic algorithm (GA) is too dependent on the initial population and a lack of local search ability. In this paper, an improved greedy genetic algorithm (IGAA) is proposed to o...
Zhenchao Wang, Haibin Duan, Xiangyin Zhang
GECCO
2008
Springer
139views Optimization» more  GECCO 2008»
13 years 9 months ago
Coordinate change operators for genetic algorithms
This paper studies the issue of space coordinate change in genetic algorithms, based on two methods: convex quadratic approximations, and principal component analysis. In both met...
Elizabeth F. Wanner, Eduardo G. Carrano, Ricardo H...
GPEM
2008
98views more  GPEM 2008»
13 years 8 months ago
Sporadic model building for efficiency enhancement of the hierarchical BOA
Efficiency enhancement techniques--such as parallelization and hybridization--are among the most important ingredients of practical applications of genetic and evolutionary algori...
Martin Pelikan, Kumara Sastry, David E. Goldberg
GECCO
2004
Springer
14 years 1 months ago
Non-stationary Subtasks Can Improve Diversity in Stationary Tasks
Low diversity in a genetic algorithm (GA) can cause the search to become stagnant upon reaching a local optimum. To some extent, non-stationary tasks avoid this problem, which woul...
Christopher Willis-Ford, Terence Soule
GECCO
2004
Springer
134views Optimization» more  GECCO 2004»
14 years 1 months ago
A Descriptive Encoding Language for Evolving Modular Neural Networks
Evolutionary algorithms are a promising approach for the automated design of artificial neural networks, but they require a compact and efficient genetic encoding scheme to repres...
Jae-Yoon Jung, James A. Reggia