COMPARATIVE ANALYSIS OF ALGORITHMS AND CRITERIA FOR OPTIMIZING RUNNER LOCATION IN INJECTION MOLDING
E.I. Kurkin, V.O. Chertykovtseva
Samara National Research University, Samara, Russia
Keywords: optimization criterion, convolution method, genetic algorithms, composite materials, injection molding
Abstract
This article describes the results of a comparative analysis of classical and modified genetic algorithms for solving the problem the optimal runner position in a thermoplastic injection mold. Based on the comparison, it was found that the modified genetic algorithm converges 25% faster than the classical algorithm and allows for finding the minimum with 55% fewer calls to the criterion function, compared to the classical implementation of the genetic optimization algorithm. The issue of selecting the best criterion for solving the runner position optimization problem on a discrete finite element computational mesh is also examined.
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