In this paper, the analysis of recent advances in genetic algorithms is discussed. The genetic
algorithms of great interest in research community are selected for analysis. This review will …

Hybrid genetic algorithms have received significant interest in recent years and are being
increasingly used to solve real-world problems. A genetic algorithm is able to incorporate …

The fourth edition of this bestselling textbook explains the principles of artificial intelligence
(AI) and its practical applications. Using clear and concise language, it provides a solid …

When solving real-world optimization problems, evolutionary algorithms often require a
large number of fitness evaluations in order to converge to the global optima. Attempts have …

Optimizing path planning for energy efficiency is critical for achieving sustainable vehicular
transportation. This paper presents a novel framework for evaluating the impact of path …

We propose a new distributed image segmentation algorithm structured as a multiagent
system composed of a set of segmentation agents and a coordinator agent. Starting from its …

Artificial intelligence has been an active branch of research for computer scientists and
psychologists for 50 years. The concept of mimicking human intelligence in a computer fuels …

Genetic algorithms facilitate the hybridization of other local search techniques to get the
optimal solution. Basically local search and genetic algorithm are two complement solutions …

Local search can be introduced into genetic algorithms to create a hybrid, but any
improvement in performance is dependent on the learning mechanism. In the Lamarckian …

The need of effective packet transmission to deliver advanced performance in wireless
networks creates the need to find shortest network paths efficiently and quickly. This paper …