The success of decoder-based evolutionary algorithms (EAs) strongly depends on the achieved locality of operators and decoders. Most approaches to investigate locality properties ...
We present a new representation for a genetic algorithm to evolve molecular structures representing possible drugs that bind to a given protein target receptor. Our representation...
Many newly discovered genes are of unknown function. DNA microarrays are a method for determining the expression levels of all genes in an organism for which a complete genome seq...
Richard J. Gilbert, Jem J. Rowland, Douglas B. Kel...
Optimization of the control parameters of genetic algorithms is often a time consuming and tedious task. In this work we take the meta-level genetic algorithm approach to control ...
This paper discusses the issues that arise in the design and implementation of an industrialstrength evolutionary-based system for the optimization of the monthly work schedules f...
We describe a genetic segmentation algorithm for image data streams and video. This algorithm operates on segments of a string representation. It is similar to both classical gene...
Patrick Chiu, Andreas Girgensohn, Wolfgang Polak, ...
This paper examines the behavioral phenomena that occur with the tuning of the binomial-3 problem. Our analysis identifies a distinct set of phenomena that may be generalizable to...
Omer A. Chaudhri, Jason M. Daida, Jonathan C. Khoo...
Interactions between evolution and lifetime learning are of great interest to studies of adaptive behaviour both in the natural world and the field of evolutionary computation. Th...
We present an "adaptive multi-start" genetic algorithm for the Euclidean traveling salesman problem that uses a population of tours locally optimized by the Lin-Kernigha...
Dan Bonachea, Eugene Ingerman, Joshua Levy, Scott ...
This paper proposes a new crossover operator for searching over discrete probability spaces. The design of the operator is considered in the light of recent theoretical insights i...