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. © 2012 Springer-Verlag GmbH Berlin Heidelberg.
CITATION STYLE
Bhattacharya, B., Mandal, K., & Chakraborty, N. (2012). Knowledge based evolutionary programming: Cultural algorithm approach for constrained optimization. In Advances in Intelligent and Soft Computing (Vol. 132 AISC, pp. 93–101). Springer Verlag. https://doi.org/10.1007/978-3-642-27443-5_11
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