Revista de Matemática: Teoría y Aplicaciones ISSN Impreso: 1409-2433 ISSN electrónico: 2215-3373

OAI: https://revistas.ucr.ac.cr/index.php/matematica/oai
Resolviendo problemas de optimización en ingeniería con Búsqueda Tabú/Dispersa
PDF (English)

Palabras clave

multiple objectives
metaheuristics
engineering optimization
múltiples objetivos
metaheurísticas
optimización en la ingeniería

Cómo citar

Beausoleil, R. P. (2017). Resolviendo problemas de optimización en ingeniería con Búsqueda Tabú/Dispersa. Revista De Matemática: Teoría Y Aplicaciones, 24(1), 157–188. https://doi.org/10.15517/rmta.v24i1.27796

Resumen

Este artículo introduce una adaptación de una Búsqueda Tabú/ Dispersa multiobjetivo para problemas de ingeniería con restricciones no lineales con valores discretos y enteros-mixtos. El problema es reducido a un problema bi-objetivo, (la función objetivo y la función de violación de las restricciones). Este enfoque elimina el uso de penalidades para manipular las restricciones. El desempeño del algoritmo fue probado con diferentes problemas conocidos de la ingeniería, incluyendo algunas funciones de optimización matemática e ingeniería estructural. Los resultados muestran que el método propuesto trabaja bien en términos de eficiencia y robustez.

https://doi.org/10.15517/rmta.v24i1.27796
PDF (English)

Citas

Akhtar, S.; Tai, K.; Ray, T. (2002) “A socio-behavioural simulation model for engineering design optimization”, Eng. Opt. 34: 341–354.

Arora, J.S. (1989) Introduction to Optimum Design. McGraw-Hill, New York.

Beausoleil, R. (2006) “MOSS Multiobjective scatter search applied to non-linear multiple criteria optimization”, European Journal of Operational Research 169: 426–449.

Beausoleil, R. (2008) “MOSS-II Tabu/Scatter Search for nonlinear multi- objective optimization”, in: Z. Michalewicz & P. Siarry (Eds.) Advance in Metaheuristics for Hard Problems. Chapter 3. Natural Computing Series, Springer Verlag.

Belegundu, A.D. (1982) “A study of mathematical programming method for structured optimization”, R.I. Dept. of Civil and Environment Engineering of Iowa, Iowa.

Cagnina, L.C.; Esquivel, S.; Coello, C.A. (2008) “Solving engineering optimization problems with the simple constrained particle swarm optimizer”, Informatica 32: 319–326.

Chen, T.Y.; Cheng, Y.L. (2008) “Global optimization using hybrid approach”, WSEAS Transactions on Mathematics 7: 254–262.

Chickermane, Chang, H.; Gea, H. (1996) “Structural Optimization using a New Local approximation”, International Journal for Numerical Method in Engineering Method 39: 829–846.

Ching-Long, S.; Shutan, H. (2008) Latest Trends on Computers (Volume II).

De Jong, K. (1975) Analysis of the Behaviour of a Class of Genetic Adaptive Systems. Ph.D. Thesis, University of Michigan, Ann Arbor MI.

Deb, K. (1991) “Optimal design of a weld beam via genetic algorithm”, AIAA Journal 29(11): 2013–2015.

Ettaouil, M.; Loqman C. (2008) “Constraint satisfaction problems solved by semidefinite relaxations”, WSEAS Transactions on Computers 7: 951–961.

Fesanghary, M.; Mahdavi, M.; Minary-Jolandan, M.; Alizadeh, Y. (2008) “Hybridizing harmony search algorithm with sequential quadratic programming for engineering optimization problems”, Computer Methods in Applied Mechanics and Engineering 197: 3080–3091.

Fogel, L.J.; Owens, A.J.: Walsh, M.J. (1966) Artificial Intelligence Through Simulated Evolution. John Wiley, Chichester UK.

Geem, Z.W.; Kim, J.H.; Loganathan, G.V. (2001) “A new heuristic optimization algorithm: harmony search”, Simulation 76(2): 60–68.

Glover, F. (1977) “Heuristic for integer programming using surrogate constraints”, Decision Sci. 8(1): 156–166.

Glover, F. (1994) “Tabu search for nonlinear and parametric optimization (with links to genetic algorithms”, Discrete Applied Mathematics 40: 231–255.

Glover, F. (2005) “Adaptive memory projection methods for integer programming”, in: Rego C. & Alidee B. (Eds.) Metaheuristics Optimization Via Memory and Evolution: Tabu Search and Scatter Search. Kluwer Academic Publishers.

Goldberg, D.E. (1989) “Genetic Algorithms in Search, Optimization and Machine Learning”. Addison Wesley, Boston MA.

Golinski, J. (1973) “An adaptive optimization system applied to machine synthesis”, Mech. Mach. Theory 8(4): 419–436.

Hernández, S. (1994) “Multi-objective structural optimisation”, in: S. Kodiyalam & M. Saxena (Eds.) Geometry and Optimisation Techniques for Structural Design, Elsevier Applied Science: 341–363.

Holland, J.H. (1975) Adaptation in Natural and Artificial Systems. University of Michigan Press, Ann Arbor MI.

Kaveh, A.; Talatahari, S. (2009) “Engineering optimization with hybrid particle swarm and ant colony optimization”, Asian Journal of Civil Engineering (Building and Housing) 10(6): 611–628.

Kirkpatrick, S.; Gelatt, D.; Vecchi, M.P. (1983) “Optimization by simulated annealing”, Science 220: 671–680.

Koza, J.R. (1990) “Genetic programming: a paradigm for genetically breeding populations of computer programs to solve problems”, Rep. No. STAN-CS-90-1314, Stanford University, Palo Alto CA.

Lee, K.S.; Geem, Z.W. (2005) “A new meta-heuristic algorithm for continuous engineering optimization: Harmony search theory and practice”, Computer Methods in Applied Mechanics and Engineering 194: 3902–3933.

Mahdavi, M.; Fesanghary, M.; Damangir, E. (2007) “An Improved Harmony Search Algorithm for Solving Optimization Problems”, Applied Mathematics and Computation 188: 1567–1579.

Parsopoulos, K.E.; Vrahatis, M.N. (2005) “Particle swarm optimization for solving constrained engineering optimization problems”, in: L. Wang, K. Chen, & Y.S. Ong (Eds.) ICNC 2005, LNCS 3612: 582–591.

Raj, K.H.; Sharma, R.S.; Mishra, G.S.; Dua, A.; Patvardhan, C. (2005) “An evolutionary computational technique for constrained optimisation in engineering design”, IE (I) Journal.MC 86.

Ray, T.; Saini, P. (2001) “Engineering design optimisation using a swarm with intelligent information sharing among individuals”, Engineering Optimisation 33: 735–748.

Sahab, M.G.; Toropov, V.V.; Ashour, A.F. (2004) “A hybrid genetic algorithm for structural optimization probems”, Asian Journal of Civil Engineering (Building and Housing) 5(3-4): 121–143.

Sandgren, E. (1990) “Nonlinear integer and discrete programming in mechanical design optimization”, J. Mech. Des. ASME 112: 223–229.

Singiresu, S.; Ying, X. (2005) Journal of Mechanical Design 127(6): 1100–1112.

Comentarios

Descargas

Los datos de descargas todavía no están disponibles.