Incorporation of gradient into random search optimization

Authors


  • Presented at the Second Canadian-German Workshop on Chemical Engineering Mathematics, Bad Honnef, Fr Germany, May 30–June 2, 1988.

Abstract

To improve the rate of convergence of random search optimization procedures, the incorporation of a gradient-oriented one-dimensional search is investigated. With this modification to the random search procedure based on uniform sampling and region contraction [1], convergence to within 0.01% of the global optimum was obtained substantially faster for typical chemical engineering problems. It was also found that the reliability of obtaining the global optimum was improved.

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