This paper presents a practical methodology of improving the efficiency of Genetic Algorithms through tuning the factors significantly affecting GA performance. This methodology is...
Andrei Petrovski, Alexander E. I. Brownlee, John A...
In this paper we present a method based on preference relations for transforming non–crisp (qualitative) relationships between objectives in multi–objective optimisation into ...
Artificial neural networks and genetic algorithms derived from the corresponding simulation of biology, anatomy. The paper analyzes the advantages and the disadvantages of the art...
Particle filters have proven to be an effective tool for visual tracking in non-gaussian, cluttered environments. Conventional particle filters however do not scale to the problem...
Jonathan Deutscher, Andrew J. Davison, Ian D. Reid
In this paper, we propose a Genetic Algorithm (GA) approach using a new paths growth procedure by the random key-based encoding for solving Shortest Path Routing (SPR) problem. An...