M.Z. Lai
College of Computer Science and Technology, Harbin University of Science and Technology, Harbin, Heilongjiang 150080, China
Z.M. Duan
HLJ Province Electronic and Information Products Supervision Inspection Institute, Harbin, Heilongjiang, 150090, China
G.Y Zhang
School of Astronautics, Harbin Institute of Technology, Heilongjiang150001, China
B.D
School of Astronautics, Harbin Institute of Technology, Heilongjiang150001, China
ABSTRACT
A kind of fast and elitist multi-objective genetic algorithm (nondominated sorting genetic algorithm -II) was presented to solve high dimension and multi-modal optimal problems. T His fuzzy information could be converted into a mathematically well-structured problem based on fuzzy optimal theory. And the improved crossover operator of NSGA-II was applied to obtain the optimal solution. According to the test results on a typical test function and an application on the structural fuzzy multi-objective optimization of three-bar truss, more reasonable distributed solutions could be obtained and the diversity of the solutions could be maintained. It provides beneficial references for engineering application of fuzzy multi-objective structure optimization.
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How to cite this article
M.Z. Lai, Z.M. Duan, G.Y Zhang and B.D, 2013. Multi-objective Structural Optimization Base on Improved NSGA-II Algorithm. Information Technology Journal, 12: 7646-7650.
DOI: 10.3923/itj.2013.7646.7650
URL: https://scialert.net/abstract/?doi=itj.2013.7646.7650
DOI: 10.3923/itj.2013.7646.7650
URL: https://scialert.net/abstract/?doi=itj.2013.7646.7650
REFERENCES
- Deb, K., S. Agrawal, A. Pratap and T. Meyarivan, 2000. A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. Proceedings of the 6th International Conference on Parallel Problem Solving from Nature, September 18-20, 2000, Paris, pp: 849-858.
CrossRef - Fonseca, C.M. and P.J. Fleming, 1995. An overview of evolutionary algorithms in multiobjective optimization. Evol. Comput., 3: 1-16.
CrossRefDirect Link - Rubenstein-Montano, B. and R.A. Malaga, 2000. A weighted sum genetic algorithm to support multiple-party multiple-objective negotiations. IEEE Trans. Evol. Comput., 6: 366-377.
CrossRef - Srinivas, N. and K. Deb, 1994. Muiltiobjective optimization using nondominated sorting in genetic algorithms. Evol. Comput., 2: 221-248.
CrossRef - Zitzler, E. and L. Thiele, 1999. Multiobjective evolutionary algorithms: A comparative case study and the strength pareto approach. IEEE Trans. Evol. Comput., 3: 257-271.
CrossRefDirect Link