A cost benefit operator for efficient multi level genetic algorithm searches

— In this paper we present a novel cost benefit operator that assists multi level genetic algorithm searches. Through the use of the cost benefit operator, it is possible to dynamically constrain the search of the base level genetic algorithm, to suit the user’s requirements. Initially we review meta-evolutionary (multi-level genetic algorithm) approaches. We note that the current literature has abundant studies on meta-evolutionary GAs. However these approaches have not identified an efficient approach to termination of base GA search or a means to balance practical consideration such as quality of solution and the expense of computation. Our Quality time tradeoff operator (QTT) is user defined, and acts as a base level termination operator and also provides a fitness value for the meta-level GA. In this manner the amount of computation time spent on less encouraging configurations can be specified by the user. Our approach has been applied to a computationally intensive test prob...

• Type: Conference
• Year: 2007
• Where: CEC
• Authors: George G. Mitchell, Barry McMullin, James Decraene
• Keywords: Artificial Intelligence, CEC 2007, Cost Benefit Operator, Genetic Algorithm, Level Genetic Algorithm