MODELLING OF A TURNING PROCESS USING THE GRAVITATIONAL SEARCH ALGORITHM

This paper proposes the modelling of a turning process using a gravitational search algorithm (GSA). GSA is an optimization algorithm based on Newton's law of universal gravitation and mass interactions. In order to sufficiently describe the turning process, at least three independent variables are required: cutting speed, feed-rate, and cutting depth. Independent variables have impacts on dependent variables, which were in our case cutting force, surface roughness, and tool-life. The values of independent and dependent variables obtained by measurements serve as a knowledge database for feeding the GSA optimization process. During our research the GSA was used for optimizing the numerical coefficients of predefined polynomial models for describing the observed output variables. The accuracies of the obtained prediction models were proved by means of a testing data set that was excluded from the training data. The research showed that the obtained results were comparable with the other optimization algorithms such as particle swarm optimization (PSO). However, the optimization time required for GSA optimization was, in certain cases, significantly shorter. (Received in December 2012, accepted in August 2013. This paper was with the authors 2 months for 2 revisions.)

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