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Boundary Search for Constrained Numerical Optimization Problems in ACO Algorithms

  • Guillermo Leguizamón
  • Carlos A. Coello Coello
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4150)

Abstract

This paper presents a novel boundary approach which is included as a constraint-handling technique in an ant colony algorithm. The necessity of approaching the boundary between the feasible and infeasible search space for many constrained optimization problems is a paramount challenge for every constraint-handling technique. Our proposed technique precisely focuses the search on the boundary region and can be either used alone or in combination with other constraint-handling techniques depending on the type and number of problem constraints. For validation purposes, an ant algorithm is adopted as our search engine. We compare our proposed approach with respect to constraint-handling techniques that are representative of the state-of-the-art in constrained evolutionary optimization using a set of standard test functions.

Keywords

Search Space Equality Constraint Constrain Optimization Problem Active Constraint Penalty Factor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Guillermo Leguizamón
    • 1
  • Carlos A. Coello Coello
    • 2
  1. 1.LIDICUniversidad Nacional de San LuisSan LuisArgentina
  2. 2.Electrical Engineering Department, Computer Science SectionEvolutionary Computation Group (EVOCINV) at CINVESTAV-IPNMéxico D.F.México

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