Evolutionary programming techniques for economic load dispatch

Evolutionary programming has emerged as a useful optimization tool for handling nonlinear programming problems. Various modifications to the basic method have been proposed with a view to enhance speed and robustness and these have been applied successfully on some benchmark mathematical problems. B...

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Bibliographic Details
Published inIEEE transactions on evolutionary computation Vol. 7; no. 1; pp. 83 - 94
Main Authors Sinha, N., Chakrabarti, R., Chattopadhyay, P.K.
Format Journal Article
LanguageEnglish
Published New York, NY IEEE 01.02.2003
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Adaptation
Algorithms
Annealing
Applied sciences
Computer science; control theory; systems
Costs
Economics
Evolutionary
Evolutionary algorithms
Exact sciences and technology
Fuel economy
Genetic mutations
Genetic programming
Materials handling
Mathematical analysis
Mathematical models
Power generation economics
Power system economics
Processor scheduling
Programming theory
Robustness
Shape
Theoretical computing
fast evolutionary programming
Gaussian process
Algorithm performance
Evolutionary algorithm
self-adaptation
Non linear programming
economic load dispatch
Mutation
Cauchy mutation
Gaussian mutation
classical evolutionary programming
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Summary:Evolutionary programming has emerged as a useful optimization tool for handling nonlinear programming problems. Various modifications to the basic method have been proposed with a view to enhance speed and robustness and these have been applied successfully on some benchmark mathematical problems. But few applications have been reported on real-world problems such as economic load dispatch (ELD). The performance of evolutionary programs on ELD problems is examined and presented in this paper in two parts. In Part I, modifications to the basic technique are proposed, where adaptation is based on scaled cost. In Part II, evolutionary programs are developed with adaptation based on an empirical learning rate. Absolute, as well as relative, performance of the algorithms are investigated on ELD problems of different size and complexity having nonconvex cost curves where conventional gradient-based methods are inapplicable.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:1089-778X
1941-0026
DOI:10.1109/TEVC.2002.806788