A new genetic algorithm for solving nonconvex nonlinear programming problems

Applied Mathematics and Computation

Volumn 199, Issue 1, 2008, Pages 186-194

  Aryanezhad, M B ^a   Hemati, Mohammad ^b  

^a IRAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Iran)

^b ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

Decomposition; Genetic algorithm; Global optimum; Nonconvex programming; Sub problems

Indexed keywords

GENETIC ALGORITHMS; MATHEMATICAL MODELS; NUMERICAL METHODS; PROBLEM SOLVING;

NONCONVEX PROBLEMS; SUB PROBLEMS;

NONLINEAR PROGRAMMING;

EID: 41949089741     PISSN: 00963003     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.amc.2007.09.047     Document Type: Article

References (17)

1. Holland J.H. Adaptation in Natural and Artificial Systems (1992), MIT Press, Cambridge, MA
2. Goldberg D.E. Genetic Algorithms in Search Optimization, and Machine Learning (1989), Addison-Wesley, Reading, MA
3. Sakawa M., and Yauchi K. An interactive fuzzy satisfying method for multiobjective nonconvex programming problems through floating point genetic algorithms. European Journal of Operational Research 117 (1999) 113-124
4. Osman M.S., Abo-sina M.A., and Mousa A.A. An effective genetic algorithm approach to multiobjective routing problems (MORPs). Applied Mathematics and Computation 163 (2005) 769-781
5. Katayama K., Sakamoto H., and Narihisa H. The efficiency of hybrid mutation genetic algorithm for the traveling salesman problem. Mathematical and Computer Modeling 31 (2000) 197-203
6. Sangit C., Cecilia C., and Lucy A.L. Genetic algorithms and traveling salesman problems. European Journal of Operational Research 93 (1996) 490-510
7. Aytug H., khouja M., and Vergara F.E. Use of genetic algorithms to solve production and operations management problems: a review. International Journal of Production Research 41 17 (2003) 3955-4009
8. Koeh J.G. New directions in genetic algorithm theory. Annuals of Operation Research 75 (1997) 49-68
9. Hillier F.S., and Lieberman G.J. Introduction to Operations Research. seventh ed. (2001), Mc-Graw Hill pp. 668
10. Hua Z., and Huang F. An effective genetic algorithm approach to large scale mixed integer programming problems. Applied Mathematics and computation 174 (2006) 897-909
11. Ashlock D. Evolutionary Computation for Modeling and Optimization, 2006 (2005), Springer Science, Business Media Inc. pp. 257
12. Nix A.E., and Vose M.D. Modeling genetic algorithms with Markov chains. Annals of Mathematics and Artificial Intelligence 5 (1992) 79-88
13. Haupt R.L., and Haupt S.E. Practical Genetic Algorithms. second ed. (2004), John Wiley & Sons INC.
14. Cerf R. Asymptotic convergence of genetic algorithms. Advances in Applied Probability 30 (1998) 521-550
15. Aytug H., and Koehler G.J. stopping criteria for finite length genetic algorithms. ORSA Journal of Computing 8 (1996) 183-191
16. Greenhalgh D. Convergence criteria for genetic algorithms. SIAM Journal of Computation 30 (2000) 269-282
17. Wang Y.J., and Zhang J.S. An efficient algorithm for large scale global optimization of continuous functions. Journal of Computational and Applied Mathematics 206 (2007) 1015-1026