The fitness landscape of a problem is the relation between the solution candidates and their reproduction probability. In order to understand optimization problems, it is essenti...
Thomas Weise, Stefan Niemczyk, Hendrik Skubch, Rol...
The fully informed particle swarm optimization algorithm (FIPS) is very sensitive to changes in the population topology. The velocity update rule used in FIPS considers all the ne...
Given the importance of optimization and informatics which are the two broad fields of research, we present an instance of Optinformatics which denotes the specialization of info...
Minh Nghia Le, Yew-Soon Ong, Quang Huy Nguyen 0001
Genetic algorithms (GAs) used in complex optimization domains usually need to perform a large number of fitness function evaluations in order to get near-optimal solutions. In rea...
This paper demonstrates the effectiveness of genetic algorithms in training stable behavior in a model of the spinoneuromuscular system (SNMS). In particular, we test the stabili...
In this work a branch prediction system which utilizes evolutionary techniques is introduced. It allows the predictor to adapt to the executed code and thus to improve its perform...
In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an approp...
Omid David-Tabibi, Moshe Koppel, Nathan S. Netanya...
Recent advances in XCS technology have shown that selfadaptive mutation can be highly useful to speed-up the evolutionary progress in XCS. Moreover, recent publications have shown...
Martin V. Butz, Patrick O. Stalph, Pier Luca Lanzi
Hereditary Repulsion (HR) is a selection method coupled with a fitness constraint that substantially improves the performance and consistency of evolutionary algorithms. This als...
We study the minimum s-t-cut problem in graphs with costs on the edges in the context of evolutionary algorithms. Minimum cut problems belong to the class of basic network optimiz...