A Combined Method for Solving the Problem of Optimizing the Production Schedule of Metal Structure Processing for Use in a Cyber-Physical Control System of a Metallurgical Enterprise

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Abstract

A generalized diagram of the main stages of the process of forming a production schedule for the processing shop of a metalwork plant is proposed. A scheme for the formation of a production plant with a description of the input and output coordinates, as well as a control variable has been built. The necessity of the process of optimization of the production plan is shown, which will reduce the time of production of products and ensure the maximum load of the equipment of the enterprise. This allows it to be used in a cyber-physical control system in the event of situations that are not foreseen at the initial stage of the formation of an optimal schedule for loading equipment in a processing shop. An informal and formalized statement of the problem of optimization of the production plan of a metalwork plant is given. The target criterion, restrictions on admissible solutions for optimizing the production plan are formulated and investigated. A combined solution algorithm is proposed, including a direct search method for a relatively small dimension and a genetic algorithm for large dimension problems. Testing of the proposed software for the Chelyabinsk plant of metal structures has been carried out. The efficiency of the optimization algorithm and the complexity of programs that implement it has been confirmed. The preferable regions for the parameters of the genetic algorithm were determined: the probabilities of crossing over and mutation, the type of crossing-over, the volume of the initial population.

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Bolshakov, A. A., Slobodyanyuk, L., Shashikhina, O., & Kovalchuk, Y. (2022). A Combined Method for Solving the Problem of Optimizing the Production Schedule of Metal Structure Processing for Use in a Cyber-Physical Control System of a Metallurgical Enterprise. In Studies in Systems, Decision and Control (Vol. 418, pp. 243–259). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-95120-7_21

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