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2011 | OriginalPaper | Buchkapitel

18. Genetic Algorithm

verfasst von : Marko Čepin

Erschienen in: Assessment of Power System Reliability

Verlag: Springer London

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Abstract

Genetic algorithm is a probabilistic search method founded on the principle of natural selection and genetic recombination. Genetic algorithm represents a powerful method that efficiently uses historical information to evaluate new search points with expected better performance. It is applicable to linear and to nonlinear problems with many local extrema. The advantages and the disadvantages of the genetic algorithm are given. The procedures for performing optimizations are explained. The flowcharts are given together with the genetic algorithm structure descriptions. The steps of the procedures are explained. Further reading of selected references is suggested because it is not possible to present in a short chapter all the features of the method with practical examples.

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Literatur
1.
Zurück zum Zitat Cedeno W (1995) The multi-niche crowding genetic algorithm: analysis and application. Doctoral dissertation, University of California Cedeno W (1995) The multi-niche crowding genetic algorithm: analysis and application. Doctoral dissertation, University of California
2.
Zurück zum Zitat Dasgupta D, Michalewicz Z (1997) Evolutionary algorithms in engineering applications. Springer, New YorkCrossRefMATH Dasgupta D, Michalewicz Z (1997) Evolutionary algorithms in engineering applications. Springer, New YorkCrossRefMATH
3.
Zurück zum Zitat Goldberg DE (1989) Genetic algorithms in search: optimization and machine learning. Addison-Wesley, Reading, MassMATH Goldberg DE (1989) Genetic algorithms in search: optimization and machine learning. Addison-Wesley, Reading, MassMATH
5.
Zurück zum Zitat Parsopoulos KE, Vrahatis MN (2002) Recent approaches to global optimization problems through Particle Swarm optimization. Nat Comput 1(2):235?306MathSciNetCrossRefMATH Parsopoulos KE, Vrahatis MN (2002) Recent approaches to global optimization problems through Particle Swarm optimization. Nat Comput 1(2):235?306MathSciNetCrossRefMATH
6.
Zurück zum Zitat Schwefel H (1995) Evolution and optimum seeking. Wiley, New York Schwefel H (1995) Evolution and optimum seeking. Wiley, New York
7.
Zurück zum Zitat De Jong KA (1975) An analysis of the behavior of a class of genetic adaptive systems. Doctoral dissertation, University of Michigan, Ann Arbor De Jong KA (1975) An analysis of the behavior of a class of genetic adaptive systems. Doctoral dissertation, University of Michigan, Ann Arbor
8.
Zurück zum Zitat Haupt RL, Haupt SE (2003) Practical genetic algorithms. Wiley, New YorkCrossRef Haupt RL, Haupt SE (2003) Practical genetic algorithms. Wiley, New YorkCrossRef
9.
Zurück zum Zitat Lee KY, El-Sharkawi MA (2008) Modern heuristic optimization techniques: theory and applications to power systems. Wiley, New YorkCrossRef Lee KY, El-Sharkawi MA (2008) Modern heuristic optimization techniques: theory and applications to power systems. Wiley, New YorkCrossRef
10.
Zurück zum Zitat Rothlauf F (2006) Representations for genetic and evolutionary algorithms. Springer, Berlin Rothlauf F (2006) Representations for genetic and evolutionary algorithms. Springer, Berlin
11.
12.
Zurück zum Zitat Melanie M (1998) An introduction to genetic algorithms. MIT, CambridgeMATH Melanie M (1998) An introduction to genetic algorithms. MIT, CambridgeMATH
13.
Zurück zum Zitat Fogel DB (2006) Evolutionary computing: toward a new philosophy of machine intelligence. Wiley, New York Fogel DB (2006) Evolutionary computing: toward a new philosophy of machine intelligence. Wiley, New York
14.
Zurück zum Zitat Kumar S, Naresh R (2007) Efficient real code genetic algorithm to solve the non-convex hydrothermal scheduling problem. Electr Power Energy Syst 29:738?747CrossRef Kumar S, Naresh R (2007) Efficient real code genetic algorithm to solve the non-convex hydrothermal scheduling problem. Electr Power Energy Syst 29:738?747CrossRef
15.
Zurück zum Zitat Volkanovski A, Mavko B, Boševski T et al (2008) Genetic algorithm optimization of the maintenance scheduling of generating units in a power system. Rel Eng Syst Saf 93:779?789CrossRef Volkanovski A, Mavko B, Boševski T et al (2008) Genetic algorithm optimization of the maintenance scheduling of generating units in a power system. Rel Eng Syst Saf 93:779?789CrossRef
16.
Zurück zum Zitat King TD, El-Hawary ME, El-Hawary F (1995) Optimal environmental dispatching of electric power systems via an improved Hopfield neural network model. IEEE Trans Power Syst 10(3):1559?1565CrossRef King TD, El-Hawary ME, El-Hawary F (1995) Optimal environmental dispatching of electric power systems via an improved Hopfield neural network model. IEEE Trans Power Syst 10(3):1559?1565CrossRef
17.
Zurück zum Zitat Simopoulos DN, Kavatza SD, Vournas CD (2007) An enhanced peak shaving method for short term hydrothermal scheduling. Energy Convers Manage 48:3018?3024CrossRef Simopoulos DN, Kavatza SD, Vournas CD (2007) An enhanced peak shaving method for short term hydrothermal scheduling. Energy Convers Manage 48:3018?3024CrossRef
18.
Zurück zum Zitat Basu M (2008) Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II. Electr Power Energy Syst 30:140?149CrossRef Basu M (2008) Dynamic economic emission dispatch using nondominated sorting genetic algorithm-II. Electr Power Energy Syst 30:140?149CrossRef
19.
Zurück zum Zitat Liang RH, Liao JH (2007) A fuzzy-optimization approach for generation scheduling with wind and solar energy systems. IEEE Trans Power Syst 22(4):1665?1674CrossRef Liang RH, Liao JH (2007) A fuzzy-optimization approach for generation scheduling with wind and solar energy systems. IEEE Trans Power Syst 22(4):1665?1674CrossRef
20.
Zurück zum Zitat Bharathi R, Kumar MJ, Sunitha D et al (2007) Optimization of combined economic and emission dispatch problem: a comparative study. IEEE Power Eng Conf 134?139 Bharathi R, Kumar MJ, Sunitha D et al (2007) Optimization of combined economic and emission dispatch problem: a comparative study. IEEE Power Eng Conf 134?139
21.
Zurück zum Zitat Crossley W, Williams EA (1997) A study of adaptive penalty functions for constrained genetic algorithm. In: AIAA 35th aerospace sciences meeting and exhibit, pp 83?97 Crossley W, Williams EA (1997) A study of adaptive penalty functions for constrained genetic algorithm. In: AIAA 35th aerospace sciences meeting and exhibit, pp 83?97
22.
Zurück zum Zitat Zhang PX, Zhao B, Cao YJ et al (2004) A novel multi-objective genetic algorithm for economic power dispatch. IEEE Universities Power Eng Conf 422?426 Zhang PX, Zhao B, Cao YJ et al (2004) A novel multi-objective genetic algorithm for economic power dispatch. IEEE Universities Power Eng Conf 422?426
23.
Zurück zum Zitat Dorigo M, Maria G (1997) Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans Evol Comput 1(1):53?66CrossRef Dorigo M, Maria G (1997) Ant colony system: a cooperative learning approach to the traveling salesman problem. IEEE Trans Evol Comput 1(1):53?66CrossRef
24.
Zurück zum Zitat Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor Holland JH (1975) Adaptation in natural and artificial systems. University of Michigan Press, Ann Arbor
Metadaten
Titel
Genetic Algorithm
verfasst von
Marko Čepin
Copyright-Jahr
2011
Verlag
Springer London
DOI
https://doi.org/10.1007/978-0-85729-688-7_18