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Article

An efficient constraint handling methodology for multi-objective evolutionary algorithms

This paper presents a new approach for solving constraint optimization problems (COP) based on the philosophy of lexicographical goal programming. A two-phase methodology for solving COP using a multiobjective strategy is used. In the first phase, the objective function is completely disregarded and...

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Main Author: Granada Echeverri, Mauricio
Other Authors: López Lezama, Jesús María, Romero Lázaro, Rubén Augusto
Format: Article
Language: eng
Published: Universidad de Antioquia, Facultad de Ingeniería 2009
Subjects:
Online Access: http://hdl.handle.net/10495/5387
Summary:
This paper presents a new approach for solving constraint optimization problems (COP) based on the philosophy of lexicographical goal programming. A two-phase methodology for solving COP using a multiobjective strategy is used. In the first phase, the objective function is completely disregarded and the entire search effort is directed towards finding a single feasible solution. In the second phase, the problem is treated as a bi-objective optimization problem, turning the constraint optimization into a two-objective optimization. The two resulting objectives are the original objective function and the constraint violation degree. In the first phase a methodology based on progressive hardening of soft constraints is proposed in order to find feasible solutions. The performance of the proposed methodology was tested on 11 well-known benchmark functions.