Abstract.Evolutionary algorithms (EAs) are iterative, heuristic search methods that have found broad application in a variety of industries. They are often applied to very complex multi-modal, multi-dimensional optimization problems where the exact functional form is unknown. EAs operate by accumulating information at each iteration, so there is an assumption of consistency in the evaluation function in traditional EA application. Many real-world optimization problems in finance and engineering involve dynamic environments where this consistency assumption does not hold. This paper discusses recent advancements in the field of evolutionary computation which have enhanced the ability of EAs to perform in dynamic environments.

Received: August 17, 2007

AMS Subject Classification: 65K10, 90C59, 68T20

Key Words and Phrases: optimization, search, evolutionary algorithm

Source: International Journal of Pure and Applied Mathematics
ISSN: 1311-8080
Year: 2008
Volume: 46
Issue: 2