DOI: https://doi.org/10.15588/1607-3274-2020-2-5

APPLICATION OF THE FISH SEARСH METHOD FOR OPTIMIZATION PLANS OF THE FULL FACTOR EXPERIMENT

N. D. Koshevoy, E. M. Kostenko, V. V. Muratov

Abstract


Context. An application of the method of searching for schools of fish to construct optimal experiment plans for cost (time) in the study of technological processes and systems that allow the implementation of an active experiment on them is proposed.

Object of study. Optimization methods for cost (time) costs of experimental designs, based on the application of a school of fish search algorithm.

Objective. To obtain optimization results by optimizing the search for schools of fish for the cost (time) costs of plans for a full factorial experiment.

Method. A method is proposed for constructing a cost-effective (time) implementation of an experiment planning matrix using algorithms for searching for schools of fish. At the beginning, the number of factors and the cost of transitions for each factor level are entered. Then, taking into account the entered data, the initial experiment planning matrix is formed. The school of fish search method is based on the rearrangement of the columns of the experiment planning matrix, based on the sum of the costs (times) of transitions between levels for each of the factors. Fish schools are formed according to the following principle: fewer schools of fish where the sum of the costs (times) of transitions between levels of factors is greater. Then, rearrangements of schools of fish located nearby in the experiment planning matrix are performed. Then the gain is calculated in comparison with the initial cost (time) of the experiment.

Results. Software has been developed that implements the proposed method, which was used to conduct computational experiments to study the properties of these methods in the study of technological processes and systems that allow the implementation of an active experiment on them. The experimental designs that are optimal in terms of cost (time) are obtained, and the winnings in the optimization results are compared with the initial cost of the experiment. A comparative analysis of optimization methods for the cost (time) costs of plans for a full factorial experiment is carried out.

Conclusions. The conducted experiments confirmed the operability of the proposed method and the software that implements it, and also allows us to recommend it for practical use in constructing optimal experiment planning matrices.


Keywords


Оptimal plan, search by school of fish, optimization, experiment planning, cost, win.

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References


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