Abstract
AbstractRandom search procedures have recently been successfully applied to the optimization of a variety of chemical engineering problems, including optimization of chemical processes by flow sheet simulation. These procedures represent the independent variables as random variables described by probability distributions. The adaptive random search procedure centers the distribution for each variable about the best search point found and examines this region for a better point. Thus, this technique has the ability of continuously moving the search region toward the optimum, which is particularly advantageous in following constraints.This study examines the efficiency of the adaptive random search technique as applied to six different problems, which have been previously solved by various other techniques.
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