USE OF KNOWLEDGE IN SELECTION AND CONTROL OF OPTIMIZATION ALGORITHMS

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Abstract
Computers have been widely used in optimization based problem solving processes to assist with the numerical computations. The widespread availability of symbolic computational tools and recent developments in artificial intelligence now make it feasible to expand the role of computers in this area. Various classes of knowledge used to improve the efficiency of the optimization processes are presented in this paper. A prototype system developed in the domain of multicriteria decision making is demonstrated. The system contains knowledge needed to select appropriate optimization algorithms, to control the solution process, and to select alternate algorithms if needed.

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