Multi-objective differential evolution - Algorithm, convergence analysis, and applications

2005 IEEE Congress on Evolutionary Computation, IEEE CEC 2005. Proceedings

Volumn 1, Issue , 2005, Pages 743-750

  Xue, Feng ^a   Sanderson, Arthur C ^b   Graves, Robert J ^c  

^a GENERAL ELECTRIC COMPANY   (United States)

^b RENSSELAER POLYTECHNIC INSTITUTE   (United States)

^c DARTMOUTH COLLEGE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CONVERGENCE OF NUMERICAL METHODS; MARKOV PROCESSES; OPTIMIZATION; PARAMETER ESTIMATION; PARETO PRINCIPLE; PROBLEM SOLVING; RANDOM PROCESSES;

DISCRETE PROBLEMS; MULTI-OBJECTIVE DIFFERENTIAL EVOLUTION (MODE); PARETO OPTIMAL FRONT; RANDOM SEARCH;

EVOLUTIONARY ALGORITHMS;

EID: 27144497780     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (31)

1. C. M. Fonseca and P. J. Fleming, "Genetic algorithms for multiobjective optimization: formulation, discussion, and generalization," in Proc. of the Fifth Int. Conf. on Genetic Algorithms, 1993, pp. 416-423.
2. _, "An overview of evolutionary algorithms in multiobjejctive optimization," Evolutionary Computation, vol. 3, no. 1, pp. 1-16, 1995.
3. C. Coello, "A comprehensive survey of evolutionary-based multiobjective optimization techniques," International Journal of Knowledge and Information Systems, vol. 1, no. 3, pp. 269-308, 1999.
4. D. Van Veldhuizen and G. Lamont, "Multiobjective evolutionary algorithms: analyzing the state-of-the-art," Evolutionary Computation, vol. 8, no. 2, pp. 125-147, 2000.
5. N. Srinivas and K. Deb, "Multiobjective optimization using nondominated sorting in genetic algorithms," Evolutionary Computation, vol. 2, no. 3, pp. 221-248, 1995.
6. J. Horn, N. Nafpliotis, and D. Goldberg, "A niched pareto genetic algorithm for multiobjective optimization," in Proc. of the First IEEE Conf. on Evolutionary Computation, 1994, pp. 82-87.
7. K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan, "A fast and elitist multiobjective genetic algorithm: Nsga-ii," IEEE Trans. of Evolutionary Computation, vol. 6, no. 2, pp. 182-197, 2002.
8. E. Zitzler and L. Thiele, "Multiobjective evolutionary algorithms: a comparative case study and the strength pareto approach," IEEE Trans. of Evolutionary Computation, vol. 3, no. 4, pp. 257-271, 1999.
9. C. Coello, D. Van Veldhuizen, and G. Lamont, Evolutionary Algorithms for Solving Multi-Objective Problems. Kluwer Academic Publishers, 2002.
10. K. Deb, Multi-Objective Optimization using Evolutionary Algorithms. John Wiley, 2001.
11. F. Xue, A. Sanderson, and R. Graves, "Multi-objective differential evolution and its application to enterprise planning," in Proc. of the IEEE Int. Conf. on Robotics and Automation, 2003.
12. _, "Pareto-based multi-objective differential evolution," in Proc. of IEEE Congress on Evolutionary Computation, 2003.
13. F. Xue, "Multi-objective differential evolution: Theory and applications," Ph.D. dissertation, Rensselaer Polytechnic Institute, 2004.
14. R. Storn and K. Price, "Differential evolution: a simple and efficient adaptive scheme for global optimization over continuous spaces," International Computer Science Institute, Berkeley, Tech. Rep. TR-95-012, 1995.
15. R. Joshi and A. Sanderson, "Minimal representation multisensor fusion using differential evolution," IEEE Trans. on Systems, Man, and Cybernetics, Part A, vol. 29, no. 1, pp. 63-76, 1999.
16. _, Multisensor Fusion: A Minimal Representation Framework. World Scientific, 1999.
17. H. A. Abbass, R. Sarker, and C. Newton, "Pde: A pareto-frontier differential evolution approach for multi-objective optimization problems," in Proc. of IEEE Congress on Evolutionary Computation, 2001, pp. 971-978.
18. N. K. Madavan, "Multiobjective optimization using a pareto differential evolution approach," in Proc. of IEEE Congress on Evolutionary Computation, 2002, pp. 1145-1150.
19. D. Goldberg, Genetic algorithms in search, optimization and machine learning. Addison-Wesley, 1989.
20. E. Zitzler, K. Deb, and L. Thiele, "Comparison of multiobjective evolutionary algorithms: empirical results," Evolutionary Computation, vol. 8, no. 2, pp. 173-195, 2000.
21. G. Rudolph, "Convergence analysis of canonical genetic algorithms," IEEE Transaction on Neural Networks, vol. 5, no. 1, pp. 96-101, 1994.
22. _, "Convergence of evolutionary algorithms in general search space," in Proc. of IEEE Int. Conf. on Evolutionary Computation, 1996, pp. 50-54.
23. J. Suzuki, "A markov chain analysis on simple genetic algorithm," IEEE Trans. on Systems, Man, and Cybernetics, vol. 25, no. 4, pp. 655-659, 1995.
24. D. Fogel, "Asymptotic convergence properties of genetic algorithms and evolutionary programming: analysis and experiments," Cybernetics and Systems, vol. 25, no. 3, pp. 389-407, 1994.
25. G. Rudolph and A. A., "Convergence properties of some multi-objective evolutionary algorithms," in Proc. of IEEE Congress on Evolutionary Computation, 2000, pp. 1010-1016.
26. G. Lawler, Introduction to stochastic processes. Chapman & Hall, 1995.
27. F. Xue, A. Sanderson, and R. Graves, "Modeling and convergence analysis of a continuous multi-objective differential evolution algorithm," in IEEE Congress on Evolutionary Computation, 2005.
28. T. Hanne, "On the convergence of multiobjective evolutionary algorithms," European Journal of Operational Research, no. 117, 1999.
29. R. Subbu and A. Sanderson, Network-based distributed planning using coevolutionary algorithms. World Scientific, 2004.
30. _, "Modeling and convergence analysis of distributed coevolutionary algorithms," IEEE Tran. of Systems, Man and Cybernetics, Part B, vol. 34, no. 2, pp. 806-822, 2004.
31. F. Xue, A. Sanderson, and R. Graves, "Multi-objective evolutionary decision support for design-supplier-manufacturing planning," in IEEE Conference on Automation Science and Engineering, 2005.