Based Cost Differential Evolution Algorithm for Multi-objective Optimization Problems
Keywords:
Differential Evolution, global numerical optimization, multi-objective optimisationAbstract
In this paper, we present A new variant of the Differential Evolution algorithm. Our proposed algorithm called Based cost Differential Evolution (Bc-DE), generated the mutant vector by adding a weighted difference of two cost function multiplied by a vector selected randomly to the best individual vector. The performance of the Bc-DE algorithm is broadly evaluated on several bound-constrained nonlinear and non-differentiable continuous numerical optimization problems and compares with the conventional DE and several others DE variants. It is demonstrated that the new method converges faster and with more certainty than many other acclaimed global optimization methods.
References
R. Storn and K. Price, "Differential evolution - a simple and efficient adaptive scheme for global optimization over continuous spaces," Technical Report, 1995, TR-95-012, ICSI,
T. Rogalsky, R. W. Derksen and S. Kocabiyik, Differential evolution in aerodynamic optimization, Proc. of 46th Annual Conference of Canadian Aeronautics and Space Institute, 1999, pp. 29-36.
S. Das and A. Konar, Automatic image pixel clustering with an improved differential evolution Applied Soft Computing 9 (2009 ), no. 1, 226-236
J. Ilonen, J. K. Kamarainen and J. Lampinen, Differential evolution training algorithm for feed-forward neural networks, Neural Processing Letters 17 (2003), no. 1, 93-105..
H. A. Abbass, and R. Sarker,: The Pareto Differential Evolution Algorithm, InternationalJournal on Artificial Intelligence Tools, Vol. 11, No. 4, (2002), 531-552
B.V. Babu, and P. G.Chakole, Mubeen, J.H.S.: Multi-objective Differential Evolution (MODE) for Optimization of Adiabatic Styrene Reactor, Chemical Engineering Science, Vol. 60 (No. 17)( 2005), 4822-4837
E. Zitzler and L. Thiele “Multiobjective Evolutionary Algorithms: A Comparative Case Study and the Strength Pareto Approachâ€, IEEE Transactions on Evolutionary Computation, 3(4):257–271, November 1999.
A. Farhang-Mehr and S. Azarm. “Diversity Assessment of Pareto Optimal Solution Sets: An Entropy Approachâ€. In Congress on Evolutionary Computation (CEC’2002), vol.1, pp. 723–728, May 2002.
J. Knowles and D. Corne “Properties of an Adaptive Archiving Algorithm for Storing Nondominated Vectors†. IEEE Transactions on Evolutionary Computation, 7(2):100–116, April 2003.
K. Deb, A. Pratap, S. Agarwal, and T. Meyarivan. “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA–IIâ€. IEEE Transactions on Evolutionary Computation, 6(2):182–197, April 2002.
K. Deb, S. Agrawal, A. Pratap, and C. Meyarivan. “A fast elitist non-dominated sorting genetic algorithm for multiobjective optimization†Nsga-iiâ€. Proceedings of the Parallel Problem Solving from Nature VI Conference, pp. 849–858, 2000.
A. Veldhuizen and G. Lamont, “On measuring multiobjective evolutionary algorithm performanceâ€, 2000 Congress on Evolutionary Computation, pp. 204–211, 2000.
J. Schott. “Fault Tolerant Design Using single and Multicriteria Genetic Algorithm Optimizationâ€. Master thesis, Department of Aeronautics and Astronautics, Institute of Technology, Cambridge, Massachusetts, 1995.
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