Overview
ABSTRACT
Methods of optimization are used to perfect an industrial or laboratory operation. Among the various strategies, direct methods of optimization do not require mathematical models, but proceed by iterative experiments to determine the operating conditions to approach the optimum of functioning. These are the sequential dichotomous, golden ratio and Fibonacci methods, if only one variable is studied, and the Simplex method when several variables are considered.
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Catherine PORTE : Doctor of Physical Sciences - Professor Emeritus EA7341 – Laboratory of Molecular Chemistry and Chemical and Energy Process Engineering at the Conservatoire National des Arts et Métiers, Paris, France
INTRODUCTION
Optimization is a set of techniques for finding the values of factors that make a response function, also known as an objective function, optimal. In mathematical terms, it corresponds to the search for the extremums of multivariate functions. In the field of applied science, it involves finding the experimental conditions that enable us to obtain the optimum response value for industrial operations or laboratory experiments.
Several optimization strategies can be applied: so-called indirect methods involving knowledge or empirical models (design of experiments) and direct methods. In this article, we only describe direct methods, which do not require the use of mathematical models and, above all, are easy to apply in the applied sciences.
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KEYWORDS
Fibbonacci method | sequential dichotomy method | golden section search
Direct optimization methods, single variable method and Simplex method.
Response function, variables and strategies
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