Effective generation of Pareto sets using genetic programming

Proceedings of the ASME Design Engineering Technical Conference

Volumn 2, Issue , 2001, Pages 783-791

  Eddy, John ^a   Lewis, Kemper ^a  

^a the State University of New York   (United States)

Author keywords

Genetic Algorithms; Heuristic Optimization; Multi Objective Optimization. MOGA; Pareto Frontiers

Indexed keywords

GENETIC ALGORITHMS; HEURISTIC METHODS; OPTIMIZATION; PRESSURE VESSELS; VECTORS; COMPUTER AIDED DESIGN; MULTIOBJECTIVE OPTIMIZATION;

HEURISTIC OPTIMIZATION; PARETO FRONTIERS; PARETO SETS; COMPLETE SOLUTIONS; LARGE SYSTEM; MEASURE OF PERFORMANCE; MULTI-OBJECTIVE DESIGN; MULTI-OBJECTIVE OPTIMIZATION PROBLEM; MULTI-OBJECTIVE PROBLEM; SINGLE OBJECTIVE;

PARETO PRINCIPLE; GENETIC PROGRAMMING;

EID: 1542435520     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (22)

1. Pareto, V., 1906, Manuale di Econòmica Polìttica, Società Editrice Libràia, Milan, Italy; translated into English by A. S. Schwier, as Manual of Political Economy, Macmillan, New York, 1971.
2. Pareto, V., 1906, Manuale di Econòmica Polìttica, Società Editrice Libràia, Milan, Italy; translated into English by A. S. Schwier, as Manual of Political Economy, Macmillan, New York, 1971.
3. Chen. W., Wiecek, M., and Zhang, J., 1999, "Quality Utility: A Compromise Programming Approach to Robust Design", ASME Journal of Mechanical Design, Vol. 121, pp. 179-187.
4. Das, I. and Dennis, J. E., 1997, "A Closer Look at Drawbacks of Minimizing Weighted Sums of Objectives for Pareto set Generation in Multicriteria Optimization Problems," Structural Optimization, Vol. 14, pp. 63-69.
5. Messac, A., Sundararaj, J. G, Tappeta R. V., and Renaud, J. E., 2000, "The Ability of Objective Functions to Generate Points on Non-Convex Pareto Frontiers," AIAA Journal, Vol. 38, pp. 1084-1091.
6. Messac, A., Melachrinoudis, E., and Sukam, C. P., 2000, "Aggregate Objective Functions and Pareto Frontiers: Required Relationships and Practical Implications," Optimization and Engineering, Kluwer Academic Publishers, Netherlands, Vol. 1, pp. 171-188.
7. Kasprzak, E. and Lewis K., 2000, "An Approach to Facilitate Decision Tradeoffs in Pareto Solution Sets," Journal of Engineering Valuation and Cost Analysis, Vol. 3, pp. 173-187.
8. Das, I. and Dennis J. E., 1998, "Normal-Boundary Intersection: A New Method for Generating the Pareto Surface in Nonlinear Multicriteria Optimization Problems," SIAM Journal on Optimization, Vol. 8, pp. 631-657.
9. st AIAA/ASME/ASCE/AHS/ASC Structures, Structural Dynamics and Materials Conference, Paper No. AIAA 2000-1666.
10. Narayanan, S., and Azarm, S., 1999, "A Multiobjective Interactive Sequential Hybrid Optimization Technique for Design Decision Making", Engineering Optimization, Vol. 32, pp. 485-500.
11. Azarm S., Reynolds, B. J., and Narayanan, S., 1999, "Comparison of Two Multiobjective Optimization Techniques with and within Genetic Algorithms," ASME Design Engineering Technical Conferences, DETC99/DAC-8584.
12. Horn, J., Nafpliotis, N., and Goldberg, D. E., 1994, "A Niched Pareto Genetic Algorithm for Multiobjective Optimization," IEEE Conference on Evolutionary Computation, Vol. 1, pp 82-87.
13. Balling, R. J., 2000, "Pareto Sets in Decision-Based Design," Engineering Valuation and Cost Analysis, Vol. 3, pp. 189-198.
14. Goldberg, D.E., 1989, Genetic Algorithms in Search, Optimization, and Machine Learning, Addison-Wesley, Reading, MA.
15. Fonseca, C. M. and Fleming, P. J., 1998, "Multiobjective Optimization and Multiple Constraint Handling with Evolutionary Algorithms - Part 1: A Unified Formulation," IEEE Transactions on Systems, Management, and Cybernetics - Part A: Systems and Humans, Vol. 28, pp. 26-37.
16. Holland, J. H., 1992, Adaptation in Natural and Artificial Systems, Fifth Printing, Cambridge, Mass., First MIT Press edition.
17. Anderson, K. S. and Hsu, Y., 1998, "Crossover Strategy For Improved Solution Space Exploration With Genetic Algorithms," ASME Design Engineering Technical Conferences, DETC98/DAC-5617.
18. Gen, M. and Cheng, R., 2000, Genetic Algorithms & Engineering Optimization, John Wiley & Sons, Inc., New York, NY.
19. Wu, J. and Azarm, S., 2000, "Metrics for Quality Assessment of a Multiobjective Design Optimization Solution Set," ASME Design Engineering Technical Conferences, DETC2000/DAC-14233.
20. Winer E. H., 1999, "Development of Visualization Techniques as an Aid in Multidisciplinary Design Optimization," Ph.D. Dissertation, Department of Mechanical and Aerospace Engineering, University at Buffalo.
21. Eddy, J., 2001, "The Use of Genetic Programming and Visualization to Facilitate Multi-Objective Design Optimization," M.S. Thesis, Department of Mechanical and Aerospace Engineering, University at Buffalo.
22. Eddy, J., K. Hacker, and K. Lewis, 2000, "Solving Computationally Expensive Optimization Problems Using Hybrid Methods in Parallel Computing Environments," 8th AIAA/USAF/NASA/ISSMO Symposium on Multidisciplinary Analysis and Optimization, Long Beach, CA, AIAA-00-4864.