Knowledge Based Evolutionary Programming: Cultural Algorithm Approach for Constrained Optimization

  • Bidishna Bhattacharya
  • Kamal Mandal
  • Niladri Chakraborty
Conference paper
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 132)

Abstract

A cultural approach to solve the problem defined by the economic load dispatch in power systems is presented in this paper. The practical problems of economic load dispatch have non-smooth cost functions with equality and inequality constraints that make the problem of finding the global optimum difficult using any mathematical approaches. Our approach is based on the concept of a cultural algorithm and is applied to constrained optimization problems in which a map of the feasible region is used to guide the search more efficiently. It combines cultural algorithm with evolutionary programming technique in such a way that a simple evolutionary programming (EP) is applied as a based level search, which can give a good direction to the optimal global region, and a domain knowledge (using the concept of cultural algorithm) is used as a fine tuning to determine the optimal solution at the final. The effectiveness and feasibility of the proposed method is tested on a practical thirteen generator system. Results obtained by the proposed method are compared with the other evolutionary methods. It is seen that the proposed method can produce comparable results.

Keywords

Particle Swarm Optimization Fuel Cost Acceptance Function Belief Space Population Space 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Bidishna Bhattacharya
    • 1
  • Kamal Mandal
    • 2
  • Niladri Chakraborty
    • 2
  1. 1.Electrical Engineering Dept.Techno IndiaSaltlakeIndia
  2. 2.Department of Power EngineeringJadavpur UniversityIndia

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