Evolutionary computation methods have been used to solve several optimization and learning problems. This paper describes an application of evolutionary computation methods to con...
—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...
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 ...
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...
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...