Recently, there has been increased interest in evolutionary computation applied to changing
optimization problems. The paper surveys a number of approaches that extend the …

This paper introduces a cultural algorithm that uses domain knowledge to improve the
performance of an evolutionary programming technique adopted for constrained …

Most research in evolutionary computation focuses on optimization of static, non-changing
problems. Many real-world optimization problems, however, are dynamic, and optimization …

This paper presents a new approach to acquiring and using problem specific knowledge
during a genetic algorithm (GA) search. A GA augmented with a case-based memory of past …

Application of evolutionary algorithms to non-stationary problems is the subject of research
discussed. We extended evolutionary algorithm by two mechanisms dedicated to non …

Many real-world multiple-objective optimization problems have objectives that change over
time. These multiple-objective optimization problems are called dynamic multiple-objective …

We use case-injected genetic algorithms (CIGARs) to learn to competently play computer
strategy games. CIGARs periodically inject individuals that were successful in past games …

Cultural Algorithm (CA) naturally contains self-adaptive components that can make it an
ideal model for use in dynamic environments through the utilization of belief space …

The rapid growth of the World Wide Web has created many challenges for both general
purpose crawling, search engines and web directories, making it difficult to find, index, and …

This paper examines the feasibility of using genetic algorithms augmented with a long term
memory to attack similar traveling salesman problems. The proposed learning system …