This paper describes an evolutionary clustering algorithm, which can partition a given dataset automatically into the optimal number of groups through one shot of optimization. The...
Selection methods in Evolutionary Algorithms, including Genetic Algorithms, Evolution Strategies ES and Evolutionary Programming, EP are compared by observing the rate of converge...
In a distributed system, a number of application tasks may need to be assigned to different processors such that the system cost is minimized and the constraints with limited reso...
This paper introduces a function that increases the amount of neutrality (inactive code in Genetic Programming) for the Artificial Ant Problem. The objective of this approach is t...
A non-dominated sorting genetic algorithm is used to evolve models of learning from different theories for multiple tasks. Correlation analysis is performed to identify parameters...