Capability planning problems are pervasive throughout many areas of human interest with prominent examples found in defense and security. Planning provides a unique context for op...
James M. Whitacre, Hussein A. Abbass, Ruhul A. Sar...
The key ideas behind most of the recently proposed Markov networks based EDAs were to factorise the joint probability distribution in terms of the cliques in the undirected graph....
The interaction among particles is a vital aspect of Particle Swarm Optimization. As such, it has a strong influence on the swarm’s success. In this study various approaches re...
Evolutionary testing denotes the use of evolutionary algorithms, e.g., Genetic Algorithms (GAs), to support various test automation tasks. Since evolutionary algorithms are heuris...
A genetic algorithm (GA) is utilised to discover known and novel PROSITE-like sequence templates that can be used to classify the sub-cellular location of eukaryotic proteins. Whi...
In recent years, the development of multi-objective evolutionary algorithms (MOEAs) hybridized with mathematical programming techniques has significantly increased. However, most...
Bio-inspired ad hoc routing is an active area of research. The designers of these algorithms predominantly evaluate the performance of their protocols with the help of simulation ...
Muhammad Saleem, Syed Ali Khayam, Muddassar Farooq
Proofs and empirical evidence are presented which show that a subset of algorithms can have identical performance over a subset of functions, even when the subset of functions is ...
Multiobjective methods are ideal for evolving a set of portfolio optimisation solutions that span a range from highreturn/high-risk to low-return/low-risk, and an investor can cho...
This paper introduces a procedure based on genetic programming to evolve XSLT programs (usually called stylesheets or logicsheets). XSLT is a general purpose, document-oriented fu...