Differential Evolution, an Alternative Approach to Evolutionary Algorithm

As a relatively new population based optimization technique, differential evolution has been attracting increasing attention for a wide variety of engineering applications including power engineering. Unlike the conventional evolutionary algorithms which depend on predefined probability distribution function for mutation process, differential evolution uses the differences of randomly sampled pairs of objective vectors for its mutation process. Consequently, the object vectors' differences will pass the objective functions topographical information toward the optimization process, and therefore provide more efficient global optimization capability. This paper aims at providing an overview of differential evolution and presenting it as an alternative to evolutionary algorithms with two application examples in power systems

[1]  Mohamed Shaaban,et al.  Total transfer capability calculations for competitive power networks using genetic algorithms , 2000, DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382).

[2]  Joong-Rin Shin,et al.  A particle swarm optimization for economic dispatch with nonsmooth cost functions , 2005, IEEE Transactions on Power Systems.

[3]  David E. Goldberg,et al.  Genetic Algorithms in Search Optimization and Machine Learning , 1988 .

[4]  R. Storn,et al.  Differential Evolution - A simple and efficient adaptive scheme for global optimization over continuous spaces , 2004 .

[5]  S. Kannan,et al.  Application and comparison of metaheuristic techniques to generation expansion planning problem , 2005, IEEE Transactions on Power Systems.

[6]  J. S. F. Barker,et al.  Simulation of Genetic Systems by Automatic Digital Computers , 1958 .

[7]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[8]  C. Su,et al.  Variable scaling hybrid differential evolution for solving network reconfiguration of distribution systems , 2005 .

[9]  Rainer Storn,et al.  Minimizing the real functions of the ICEC'96 contest by differential evolution , 1996, Proceedings of IEEE International Conference on Evolutionary Computation.

[10]  Kit Po Wong,et al.  A Technique for Improving the Convergence Characteristic of Genetic Algorithms and Its Application to a Genetic-Based Load Flow Algorithm , 1996, SEAL.

[11]  P. Vadstrup,et al.  Parameter identification of induction motors using differential evolution , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[12]  Arthur C. Sanderson,et al.  Pareto-based multi-objective differential evolution , 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

[13]  Thomas Bäck,et al.  Evolutionary algorithms in theory and practice - evolution strategies, evolutionary programming, genetic algorithms , 1996 .

[14]  Kenneth V. Price,et al.  An introduction to differential evolution , 1999 .

[15]  K. Price.  Differential evolution vs. the functions of the 2/sup nd/ ICEO , 1997, Proceedings of 1997 IEEE International Conference on Evolutionary Computation (ICEC '97).

[16]  Dimitris K. Tasoulis,et al.  Parallel differential evolution , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[17]  Carlos A. Coello Coello,et al.  Culturizing differential evolution for constrained optimization , 2004, Proceedings of the Fifth Mexican International Conference in Computer Science, 2004. ENC 2004..

[18]  Jouni Lampinen,et al.  A Trigonometric Mutation Operation to Differential Evolution , 2003, J. Glob. Optim..

[19]  Kit Po Wong,et al.  Special issue on evolutionary computation for systems and control applications , 2004, Int. J. Syst. Sci..

[20]  Kitpo Wong,et al.  Advanced constrained genetic algorithm load flow method , 1999 .

[21]  John H. Holland,et al.  Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence , 1992 .

[22]  Kit Po Wong,et al.  Virtual Population and Acceleration Techniques for Evolutionary Power Flow Calculation in Power Systems , 2003 .

[23]  K. V. Price,et al.  Differential evolution: a fast and simple numerical optimizer , 1996, Proceedings of North American Fuzzy Information Processing.

[24]  A.L. Sangiovanni-Vincentelli,et al.  A survey of optimization techniques for integrated-circuit design , 1981, Proceedings of the IEEE.

[25]  Ji-Pyng Chiou,et al.  Ant direction hybrid differential evolution for solving large capacitor placement problems , 2004 .

[26]  Lawrence J. Fogel,et al.  Artificial Intelligence through Simulated Evolution , 1966 .