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Article title HYBRID ALGORITHM OF SOLVING THE PROBLEMS OF OPERATIONAL PLANNING OF THE PRODUCTION PROCESS
Authors L. A. Gladkov, N. V. Gladkova, S. A. Gromov
Section SECTION II. DESIGNING MANAGEMENT INFORMATION AND AUTOMATED SYSTEMS
Month, Year 09, 2017 @en
Index UDC 658.512.2.011.5
DOI
Abstract The article considers a new approach to solving the problems of operational planning of the production process. The definition of the task of operational planning of production is given. The place of the tasks of operational planning in the general theory of schedules is shown. The formulation of the task of operational planning for machine-building enterprises is given, specifics of the solution of such tasks at machine-building enterprises are noted, constraints and the objective function of the optimization problem are given. The structure of the proposed hybrid algorithm for operational planning of the production process is described. A method for coding solutions for using them in a hybrid algorithm is developed. The chromosome structure is described, which is a set of tasks for the planning period or the operational plan as a whole. New modifications of genetic operators aimed at increasing the diversity of the current population and overcoming local optima are proposed. Examples of implementation of modified genetic operators that take into account the specifics of solving operational planning problems are given. The proposed methodology and the sequence of calculation of the value of the criterion for assessing the quality of the solutions obtained are described. Additional restrictions were introduced on the area of feasible solutions to the problem and a methodology for calculating fines for violating established restrictions was proposed. The sequence of operations and the structure of the developed algorithm are given. A hybrid model of the algorithm based on integration of methods of genetic search and principles of fuzzy control is proposed. The characteristics of the developed algorithm are studied and its time complexity is determined. A series of computational experiments was conducted to analyze and compare the quality of the solutions obtained, as well as to determine the best values of the control parameters of the algorithm. Based on the analysis, conclusions are drawn about the merits and demerits of the proposed algorithm.

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Keywords Operational production planning problems; genetic algorithm; fuzzy logic; scheduling theory; optimization; hybrid algorithm.
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