Abstract
Optimization is being increasing applied to engineering design problems throughout the world. iSIGHT is a generic engineering design environment that provides engineers with an optimization toolkit of leading optimization algorithms and an optimization advisor to solve their optimization needs. This paper focuses on the key role played by the toolkit’s genetic algorithm in providing a robust, general purpose solution to nonlinear continuous, mixed integer nonlinear and integer combinatorial problems. The robustness of the genetic algorithm is demonstrated on successful application to 30 engineering benchmark problems and the following three real world problems: a marine naval propeller, a heart pacemaker and a jet engine turbine airfoil.
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References
Engineous Software Incorporated. www.engineous.com
Vanderplaats, G.: Numerical Optimization Techniques for Engineering Design. (1999).
Belegund, A. and Chandrupatla, T.: Optimization Concepts and Applications in Engineering. Prentice Hall (1999)
Onwubiko, C.: Introduction to Engineering Design Optimization. Prentice Hall (2000)
Gen, M. and Cheng, R: Genetic Algorithms and Engineering Optimization. John Wiley & Sons (2000).
Deb, K.: Multi-Objective Optimization Using Evolutionary Algorithms. John Wiley & Sons (2001).
Back, T.: A Users Guide to GENEsYs 1.0. University of Dortumnd. (1992)
Hiroyasu, T.: Spec Sheet: Distributed Genetic Algorithms ga2k (ver 1.1). Intelligent Systems Design Lab. Doushisya University (2002)
Inger, L.: Adaptive Simulated Annealing. http://www.ingber.com/. (2002)
Vanderplaats, G.: ADS — A Fortran Program for Automated Design Synthesis. Santa Barbara, CA: Engineering Design Optimization, Inc. (1988)
Johnson, M.: Hooke and Jeeves Algorithm. http://www.netlib.org/opt/hooke.c (1994)
Spellucci, P.: Donlp2 User Guide. http://www.netlib.org/opt/donlp2/donlp2doc.ps
Schittkowski, K.: NLPQL: A Fortran subroutine for solving constrained non linear programs. Annals of Operations Research, Vol.5, (1985–1986) 4850–500
Tseng, C.: MOST 1.1. Applied Optimal Design Laboratory, National Chiao Tung Univeristy, Technical Report AODL-9-01 (1996)
Smith, S. and Lasdon, L.: Solving large sparse nonlinear programs using GRG. ORSA J. Comput. 4, (1992) 1–15
Tanese, R.: Distributed genetic algorithms. Proceedings of the Third International Conference on Genetic Algorithms, (1989) 434–439.
Sandgren, E.: The utility of nonlinear programming algorithms. Purdue University Ph.D. Thesis, West Lafayette, IN (1977).
Sandgren, E.: Nonlinear integer and discrete programming in mechanical design optimization. Transactions of the ASME, Journal of Mechanical Design, 112(2), (1990) 223–229
Fylstra, D., Lasdon, L., Watson, J. and Waren, A.: Design and Use of the Microsoft Excel Solver. Interfaces 28 (1998) 29–55.
Furse, C.: Design an Antenna for Pacemaker Communication. Microwaves & RF, March (2000)
Powell, D.: Inter-GEN: A hybrid approach to engineering design optimization. Rensselaer Polytechnic Institute Ph.D. Thesis, Troy, NY (1990).
Vanderplaats, G.: Numerical Optimization Techniques for Engineering Design. (1999) 317–320.
Powell, D., Skolnick, M., and Tong, S.: Interdigitation: A Hybrid Technique for Engineering Design Optimization. Handbook of Genetic Algorithms. Van Nostrand Reinhold. (1991) 312–331.
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Tong, S., Powell, D.J. (2003). Genetic Algorithms: A Fundamental Component of an Optimization Toolkit for Improved Engineering Designs. In: Cantú-Paz, E., et al. Genetic and Evolutionary Computation — GECCO 2003. GECCO 2003. Lecture Notes in Computer Science, vol 2724. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45110-2_127
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DOI: https://doi.org/10.1007/3-540-45110-2_127
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