Simulation optimization based on surrogate model and genetic algorithm

Kongzhi yu Juece/Control and Decision

Volumn 19, Issue 6, 2004, Pages 626-630

  Wang, Ling ^a   Ji, Li Jun ^b   Zheng, Da Zhong ^a  

^a TSINGHUA UNIVERSITY   (China)

^b INSTITUTE OF AUTOMATION   (China)

Author keywords

Genetic algorithm; Neural network; Simulation optimization; Surrogate model

Indexed keywords

SIMULATION OPTIMIZATION; SURROGATE MODEL;

COMPUTER SIMULATION; GENETIC ALGORITHMS; NEURAL NETWORKS; PRESSURE VESSELS; PRODUCT DESIGN;

OPTIMIZATION;

EID: 4344573916     PISSN: 10010920     EISSN: None     Source Type: Journal    
DOI: None     Document Type: Article

References (16)

1. Wang L, Zhang L, Zheng D Z. Advances in simulation optimization[J]. Control and Decision, 2003, 18(3): 257-262, 271.
2. Salami M, Hendtlass T. A fast evaluation strategy for evolutionary algorithm[J]. Applied Soft Computing J, 2003, 2(3): 156-173.
3. Jin Y, Olhofer M. A framework for evolutionary optimization with approximate fitness functions [J]. IEEE Trans on Evolutionary Computation, 2002, 6(5): 481-494.
4. Rumelhart D E, McClelland J L. Parallel Distributed Processing [M]. Cambridge: MIT Press, 1986.
5. Keys A C, Rees L P, Greenwood A G. Performance measures for selection of metamodels to be used in simulation optimization [J]. Decision Sciences, 2002, 33(l): 31-57.
6. Sandgren E. Nonlinear integer and discrete programming in mechanical engineering systems [J]. J of Mechanical Design, 1990, 112(1): 223-229.
7. Fu J, Fenton R G, Cleghorn W L. A mixed integer-discrete-continuous programming method and its application to engineering design optimization[J]. Engineering Optimization, 1991, 19(4): 263-280.
8. Qian Z, Yu J, Zhou J. A genetic algorithm for solving mixed discrete optimization problems [J]. Advances in Design Automation, 1993, 65(1): 499-503.
9. Kannan B K, Kramer S N. An augmented Lagrange multiplier based method for mixed integer discrete continues optimization and its applications to mechanical design[J]. J of Mechanical Design, 1994, 116(2): 405-411.
10. Li H L, Chou C T. A global approach for nonlinear mixed discrete programming in design optimization [J]. Engineering Optimization, 1994, 22(2): 109-122.
11. Coello C A C. Use of a self-adaptive penalty approach for engineering optimization problems [J]. Computers in Industry, 2000, 41(2): 113-127.
12. Thierauf G, Jianbo C. Parallel evolution strategy for solving structural optimization[J]. Engineering Structures, 1997, 19(4): 318-324.
13. Augusto O B, Kawano A. A mixed continuous and discrete nonlinear constrained algorithm for optimizing ship null structural design [J]. Ocean Engineering, 1998, 25(9): 793-811.
14. Nakayama H, Arakawa M, Sasaki R. Simulation-based optimization using computational intelligence [J]. Optimization and Engineering, 2002, 3(2): 201-214.
15. Coello C A C, Montes E M. Constraint-handling in genetic algorithms through the use of dominance-based tournament selection [J]. Advanced Engineering Informatics, 2002, 16(3): 193-203.