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ICTAI
2009
IEEE
14 years 2 months ago
Evolution Strategies for Constants Optimization in Genetic Programming
Evolutionary computation methods have been used to solve several optimization and learning problems. This paper describes an application of evolutionary computation methods to con...
César Luis Alonso, José Luis Monta&n...
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
2005
Springer
140views Optimization» more  GECCO 2005»
14 years 1 months ago
Multi-niche crowding in the development of parallel genetic simulated annealing
In this paper, a new hybrid of genetic algorithm (GA) and simulated annealing (SA), referred to as GSA, is presented. In this algorithm, SA is incorporated into GA to escape from ...
Zhi-Gang Wang, Mustafizur Rahman 0002, Yoke-San Wo...
CSB
2003
IEEE
152views Bioinformatics» more  CSB 2003»
14 years 1 months ago
A Parallel Genetic Algorithm for Physical Mapping of Chromosomes
Physical map reconstruction in the presence of errors is a central problem in genetics of high computational complexity. A parallel genetic algorithm for a maximum likelihood esti...
Suchendra M. Bhandarkar, Jinling Huang, Jonathan A...
GECCO
2008
Springer
157views Optimization» more  GECCO 2008»
13 years 9 months ago
Self-adaptive mutation rates in genetic algorithm for inverse design of cellular automata
Self-adaptation is used a lot in Evolutionary Strategies and with great success, yet for some reason it is not the mutation adaptation of choice for Genetic Algorithms. This poste...
Ron Breukelaar, Thomas Bäck