Solving multimodal problems via multiobjective techniques with Application to phase equilibrium detection

Abstract— For solving multimodal problems by means of evolutionary algorithms, one often resorts to multistarts or niching methods. The latter approach the question: ‘What is elsewhere?’ by an implicit second criterion in order to keep populations distributed over the search space. Induced by a practical problem that appears to be simple but is not easily solved, a multiobjective algorithm is proposed for solving multimodal problems. It employs an explicit diversity criterion as second objective. Experimental comparison with standard methods suggests that the multiobjective algorithm is fast and reliable and that coupling it with a local search technique is straightforward and leads to enormous quality gain. The combined algorithm is still fast and may be especially valuable for practical problems with costly target function evaluations.

• Type: Conference
• Year: 2007
• Where: CEC
• Authors: Mike Preuss, Günter Rudolph, Feelly Tumakaka
• Keywords: Artificial Intelligence, CEC 2007, Multimodal Problems, Multiobjective Algorithm, Practical Problems