Solving optimization problems with multiple (often conflicting) objectives is, generally, a very difficult goal. Evolutionary algorithms (EAs) were initially extended and applied ...
Two efficient clustering-based genetic algorithms are developed for the optimisation of reaction rate parameters in chemical kinetic modelling. The genetic algorithms employed are ...
Lionel Elliott, Derek B. Ingham, Adrian G. Kyne, N...
Finding a good wavelet for a particular application and type of input data is a difficult problem. Traditional methods of wavelet deus on abstract properties of the wavelet that ca...
This paper describes a collection of algorithms that we developed and implemented to facilitate the automatic recovery of the modular structure of a software system from its sourc...
Spiros Mancoridis, Brian S. Mitchell, C. Rorres, Y...
Differential evolution (DE) has emerged as one of the fast, robust, and efficient global search heuristics of current interest. This paper describes an application of DE to the aut...