A new meta-heuristic algorithm for continuous engineering optimization: harmony search theory and practice

Computer Methods in Applied Mechanics and Engineering - Tập 194 - Trang 3902-3933 - 2005
Kang Seok Lee1, Zong Woo Geem2
1Materials and Construction Research Division, Building and Fire Research Laboratory, National Institute of Standards and Technology, Gaithersburg, MD 20899-8611, USA
2Department of Civil and Environmental Engineering, University of Maryland, College Park, MD 20742, USA

Tài liệu tham khảo

Fogel, 1966 K. De Jong, Analysis of the behavior of a class of genetic adaptive systems, Ph.D. Thesis, University of Michigan, Ann Arbor, MI, 1975. J.R. Koza, Genetic programming: a paradigm for genetically breeding populations of computer programs to solve problems, Rep. No. STAN-CS-90-1314, Stanford University, CA, 1990. Holland, 1975 Goldberg, 1989 Glover, 1977, Heuristic for integer programming using surrogate constraints, Decision Sci., 8, 156, 10.1111/j.1540-5915.1977.tb01074.x Kirkpatrick, 1983, Optimization by simulated annealing, Science, 220, 671, 10.1126/science.220.4598.671 Geem, 2001, A new heuristic optimization algorithm: harmony search, Simulation, 76, 60, 10.1177/003754970107600201 Metropolis, 1953, Equations of state calculations by fast computing machines, J. Chem. Phys., 21, 1087, 10.1063/1.1699114 Pincus, 1970, A Monte Carlo method for the approximate solution of certain types of constrained optimization problems, Oper. Res., 18, 1225, 10.1287/opre.18.6.1225 Schwefel, 1994, On the evolution of evolutionary computation, 116 Kennedy, 1995, Particle swarm optimization, 1942 M. Pelikan, D.E. Goldberg, F.G. Lobo, A survey of optimization by building and using probabilistic models, IlliGAL Rep. No. 99018, University of Illinois Genetic Algorithms Laboratory, Urbana, IL, 1999. Larranaga, 2002 O. Jiri, Parallel estimation of distribution algorithms, Ph.D. Thesis, BRNO University of Technology, Czech Republic, 2002. S. Baluja, Population-based incremental learning: a method for integrating genetic search based function optimization and competitive learning, Technical Report No. CMU-CS-94-163, Carnegie Mellon University, PA, 1994. Muhlenbein, 1997, The equation for response to selection and its use for prediction, Evolution. Comput., 5, 303, 10.1162/evco.1997.5.3.303 Harik, 1998, The compact genetic algorithm, 523 De Bonet, 1997, MIMC: finding optima by estimating probability densities Baluja, 1997, Using optimal dependency-trees for combinatorial optimization: learning the structure of the search space, 30 Pelikan, 1999, The bivariate marginal distribution algorithm, 521 G. Harik, Lingkage learning via probabilistic modeling in the ECGA, IlliGAL Rep. No. 99010, University of Illinois Genetic Algorithms Laboratory, Urbana, IL, 1999. Muhlenbein, 1999, Convergence theory and applications of the factorized distribution algorithm, J. Comput. Inform. Technol., 7, 19 Pelikan, 1999, BOA: the Bayesian optimization algorithm, vol. I, 525 Muhlenbein, 1999, FDA-A scalable evolutionary algorithm for the optimization of additively decomposed functions, Evolution. Comput., 7, 353, 10.1162/evco.1999.7.4.353 R. Etxeberria, P. Larranaga, Global optimization with Bayesian networks, in: II Symposium on Artificial Intelligence (CIMAF99), Special Session on Distributions and Evolutionary Optimization, 1999, pp. 332–339. Dixon, 1975 Rosenbrock, 1960, An automatic method for finding the greatest or least value of a function, Comput. J., 3, 175, 10.1093/comjnl/3.3.175 Goldstein, 1971, On descent from local minima, Math. Comput., 25, 569, 10.1090/S0025-5718-1971-0312365-X Eason, 1974, A comparison of numerical optimization methods for engineering design, ASME J. Engrg. Ind., 96, 196, 10.1115/1.3438296 A.R. Colville, A comparative study of nonlinear programming, Tech. Report No. 320-2949, IBM New York Scientific Center, 1968. Conn, 1997, On the convergence of derivative-free methods for unconstrained optimization Bracken, 1968 Homaifar, 1994, Constrained optimization via genetic algorithms, Simulation, 62, 242, 10.1177/003754979406200405 Fogel, 1995, A comparison of evolutionary programming and genetic algorithms on selected constrained optimization problems, Simulation, 64, 399, 10.1177/003754979506400605 Deb, 2000, An efficient constraint handling method for genetic algorithms, Comput. Methods Appl. Mech. Engrg., 186, 311, 10.1016/S0045-7825(99)00389-8 Michalewicz, 1996, Evolutionary algorithms for constrained parameter optimization problems, Evolution. Comput., 4, 1, 10.1162/evco.1996.4.1.1 Himmelblau, 1972 Coello, 2000, Use of a self-adaptive penalty approach for engineering optimization problems, Comput. Ind., 41, 113, 10.1016/S0166-3615(99)00046-9 Shi, 1998, A modified particle swarm optimizer, 69 Michalewicz, 1995, Genetic algorithms, numerical optimization, and constraints, 151 Sandgren, 1990, Nonlinear integer and discrete programming in mechanical design optimization, J. Mech. Des. ASME, 112, 223, 10.1115/1.2912596 Wu, 1995, Genetic algorithms for nonlinear mixed discrete-integer optimization problems via meta-genetic parameter optimization, Engrg. Optim., 24, 137, 10.1080/03052159508941187 Reklaitis, 1983 Siddall, 1972 Ragsdell, 1976, Optimal design of a class of welded structures using geometric programming, ASME J. Engrg. Ind. Ser. B, 98, 1021, 10.1115/1.3438995 Deb, 1991, Optimal design of a welded beam via genetic algorithms, AIAA J., 29, 10.2514/3.10834 Topping, 1983, Shape optimization of skeletal structures: a review, ASCE J. Struct. Engrg., 109, 1933, 10.1061/(ASCE)0733-9445(1983)109:8(1933) Schmit, 1974, Some approximation concepts for structural synthesis, AIAA J., 12, 692, 10.2514/3.49321 L.A. Schmit Jr., H. Miura, Approximation concepts for efficient structural synthesis, NASA CR-2552, NASA, Washington, DC, 1976. Venkayya, 1971, Design of optimum structures, Comput. Struct., 1, 265, 10.1016/0045-7949(71)90013-7 Dobbs, 1976, Application of optimality criteria to automated structural design, AIAA J., 14, 1436, 10.2514/3.7232 P. Rizzi, Optimization of multi-constrained structures based on optimality criteria, in: Conference on AIAA/ASME/SAE 17th Structures, Structural Dynamics, and Materials, King of Prussia, PA, 1976. Khan, 1979, An optimality criterion method for large-scale structures, AIAA J., 17, 753, 10.2514/3.61214 Imai, 1981, Configuration optimization of trusses, ASCE J. Struct. Div., 107, 745, 10.1061/JSDEAG.0005702 J.E. Felix, Shape optimization of trusses subjected to strength, displacement, and frequency constraints, Master ’s Thesis, Naval Postgraduate School, 1981. J.P. Yang, Development of genetic algorithm-based approach for structural optimization, Ph.D. Thesis, Nanyang Technology University, Singapore, 1996. Soh, 1996, Fuzzy controlled genetic algorithm search for shape optimization, ASCE J. Comput. Civ. Engrg., 10, 143, 10.1061/(ASCE)0887-3801(1996)10:2(143) Rajeev, 1997, Genetic algorithm-based methodologies for design optimization of trusses, ASCE J. Struct. Engrg., 123, 350, 10.1061/(ASCE)0733-9445(1997)123:3(350) Yang, 1997, Structural optimization by genetic algorithms with tournament selection, ASCE J. Comput. Civ. Engrg., 11, 195, 10.1061/(ASCE)0887-3801(1997)11:3(195) Gill, 1978, Flood routing by the Muskingum method, J. Hydrol., 36, 353, 10.1016/0022-1694(78)90153-1 Tung, 1985, River flood routing by nonlinear Muskingum method, J. Hydraul. Engrg. ASCE, 111, 1147, 10.1061/(ASCE)0733-9429(1985)111:12(1447) Yoon, 1993, Parameter estimation of linear and nonlinear Muskingum models, J. Water Resour. Plan. Manage. ASCE, 119, 600, 10.1061/(ASCE)0733-9496(1993)119:5(600) Mohan, 1997, Parameter estimation of nonlinear Muskingum models using genetic algorithm, J. Hydraul. Engrg. ASCE, 123, 137, 10.1061/(ASCE)0733-9429(1997)123:2(137)