Comparing bio-inspired algorithms in constrained optimization problems

Abstract— This paper presents a comparison of four bioinspired algorithms (all seen as search engines) with a similar constraint-handling mechanism (Deb’s feasibility rules) to solve constrained optimization problems. The aim is to analyze the performance of traditional versions of each algorithm based on both, final results and on-line behavior. A set of 24 wellknown benchmark problems are used in the experiments. Quality and consistency of results per each algorithm are investigated. Furthermore, two performance measures (number of evaluations to reach a feasible solution and progress ratio inside the feasible region) are utilized to compare the on-line behavior of each approach. Based on the obtained results, some conclusions are established.

• Type: Conference
• Year: 2007
• Where: CEC
• Authors: Efrén Mezura-Montes, Blanca Cecilia Lopez-Ramirez
• Keywords: Artificial Intelligence, CEC 2007, Constrained Optimization Problems, Deb’s Feasibility Rules, On-line Behavior