Solving deceptive problems using a genetic algorithm with reserve selection

— Deceptive problems are a class of challenging problems for conventional genetic algorithms (GAs), which usually mislead the search to some local optima rather than the global optimum. This paper presents an improved genetic algorithm with reserve selection to solve deceptive problems. The concept “potential” of individuals is introduced as a new criterion for selecting individuals for reproduction, where some individuals with low fitness are also let survive only if they have high potentials. An operator called adaptation is further employed to release the potentials for approaching the global optimum. Case studies are done in two deceptive problems, demonstrating the effectiveness of the proposed algorithm.

• Type: Conference
• Year: 2008
• Where: CEC
• Authors: Yang Chen, Jinglu Hu, Kotaro Hirasawa, Songnian Yu
• Keywords: Artificial Intelligence, CEC 2008, Deceptive Problems, Genetic Algorithm, Global Optimum