Abstract
This paper presents a particle swarm optimizer to solve constrained optimization problems. The proposed approach adopts a simple method to handle constraints of any type (linear, nonlinear, equality and inequality), and it also presents a novel mechanism to update the velocity and position of each particle. The approach is validated using standard test functions reported in the specialized literature and it’s compared with respect to algorithms representative of the state-of-the-art in the area. Our results indicate that the proposed scheme is a promising alternative to solve constrained optimization problems using particle swarm optimization.
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Cagnina, L., Esquivel, S., Gallard, R.: Particle swarm optimization for sequencing problems: a case study. In: Congress on Evolutionary Computation, Portland, Oregon, USA, pp. 536–541 (2004), http://www.lidic.unsl.edu.ar/publicaciones/info_publicacion.php?id_publicacion=200
Coello Coello, C.A.: Theoretical and Numerical Constraint Handling Techniques used with Evolutionary Algorithms: A Survey of the State of the Art. Computer Methods in Applied Mechanics and Engineering 191(11-12), 1245–1287 (2002)
Eberhart, R., Shi, Y.: A modified particle swarm optimizer. In: International Conference on Evolutionary Computation, IEEE Service Center, Anchorage, Piscataway (1998)
Kennedy, J.: Small world and mega-minds: effects of neighborhood topologies on particle swarm performance. In: 1999 Congress on Evolutionary Computation, pp. 1931–1938. IEEE Service Center, Piscataway (1999)
Kennedy, J.: Bare bones particle swarms. In: IEEE Swarm Intelligence Symposium, pp. 80–87 (2003)
Kennedy, J., Eberhart, R.C.: Swarm Intelligence. Morgan Kaufmann Publishers, California (2001)
Parsopoulos, K.E., Vrahatis, M.N.: Unified particle swarm optimization for solving constrained engineering optimization problems. LNCS, pp. 582–591. Springer, Berlin, Heidelberg (2005)
Rao, S.S.: Engineering Optimization, 3rd edn. John Wiley & Sons, Chichester (1996)
Runarsson, T.P., Yao, X.: Stochastic ranking for constrained evolutionary optimization. IEEE Transactions on Evolutionary Computation 3, 284–294 (2000)
Toscano Pulido, G., Coello Coello, C.A.: A constrained-handling mechanism for particle swarm optimization. In: Congress on Evolutionary Computation, Portland, Oregon, USA, pp. 1396–1403 (2004)
Zhang, W., Xie, X., Bi, D.: Handling boundary constraints for numerical optimization by particle swarm flying in periodic search space. In: Congress on Evolutionary Computation, Portland, Oregon, USA, pp. 2307–2311 (2004)
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Cagnina, L.C., Esquivel, S.C., Coello, C.A.C. (2006). A Particle Swarm Optimizer for Constrained Numerical Optimization. In: Runarsson, T.P., Beyer, HG., Burke, E., Merelo-GuervĂ³s, J.J., Whitley, L.D., Yao, X. (eds) Parallel Problem Solving from Nature - PPSN IX. PPSN 2006. Lecture Notes in Computer Science, vol 4193. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11844297_92
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DOI: https://doi.org/10.1007/11844297_92
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-38990-3
Online ISBN: 978-3-540-38991-0
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