Differential Evolution with Self-adaptation and Local Search for Constrained Multiobjective Optimization

— This paper presents Differential Evolution with Self-adaptation and Local Search for Constrained Multiobjective Optimization algorithm (DECMOSA-SQP), which uses the self-adaptation mechanism from DEMOwSA algorithm presented at CEC 2007 and a SQP local search. The constrained handling mechanism is also incorporated in the new algorithm. Assessment of the algorithm using CEC 2009 special session and competition on constrained multiobjective optimization test functions is presented. The functions are composed of unconstrained and constrained problems. Their results are assessed using the IGD metric. Based on this metric, algorithm strengths and weaknesses are discussed.

• Type: Conference
• Year: 2009
• Where: CEC
• Authors: Ales Zamuda, Janez Brest, Borko Boskovic, Viljem Zumer
• Keywords: Algorithm, Artificial Intelligence, CEC 2009, Constrained Multiobjective Optimization, Multiobjective Optimization Algorithm