Article

Article title SOLVING OF TASKS OF PRODUCTION PLANNING BASED ON HYBRID EVOLUTIONARY METHODS
Authors L.A. Gladkov, N.V. Gladkova, M.Y. Lavrik
Section SECTION II. BIOINSPIRED SEARCH
Month, Year 07, 2016 @en
Index UDC
DOI DOI 10.18522/2311-3103-2016-7-6273
Abstract The paper considers methods for solving problems of planning of the production process. Classification of scheduling problems. We list the main types of planning tasks, enabling the devel-opment of plans for different periods. Considered in detail the problem of operational production planning. Identified challenges that need to be addressed in the planning process. The conditions of construction and operational planning problem solving. An example of a problem of construction schedule of the production process. Showing examples of display solutions in the process graphically. The problem of plotting the production process in terms of scheduling problems. The basic criteria and constraints used in the production planning and solving problems. The requirements to a set of input data required for the successful solution of the problem. A mathematical formulation of the problem of operational planning of the production process. Formulated and describes the main criteria for assessing the quality of the solutions. A genetic algorithm to search and optimization solutions in the construction schedule of the production process. A description of the sequence of execution of the genetic algorithm operations. plotting the manufacturing process. This paper proposes a new hybrid method for solving the planning problem based on genetic algorithms and fuzzy logic controller models. The description used by PLC rules, the structure of the proposed algorithm. Examples of fuzzy rules used in the hybrid algorithm. The block diagram of the hybrid algorithm developed operational planning of production. Based on the proposed algorithm, developed a program for solving the problem of construction time schedule of the production process. A brief description of computational experiments confirming the effectiveness of the proposed method.

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Keywords The time schedule of production; operational planning; evolutionary computations; fuzzy genetic algorithms; fuzzy logic controller.
References 1. Lazarev A.A., Gafarov E.R. Teoriya raspisaniy. Zadachi i algoritmy [The scheduling theory. Problems and algorithms]. Moscow: Izd-vo MGU, 2011, 222 p.
2. Takhonov I.I. Vvedenie v teoriyu raspisaniy [Introduction to the theory of schedules]. Novosi-birsk: Izd-vo NGU, 2011.
3. Gavrilova T.A., Muromtsev D.I. Intellektual'nye tekhnologii v menedzhmente [Intelligent technologies in management]. St. Petersburg: Vysshaya shkola menedzhmenta, 2008, 498 p.
4. Kuznetsov A.I., Kolobov A.A., Omel'chenko I.N. Tekhnologiya biznes-planirovaniya [Technol-ogy business planning]. Moscow: MGTU im. N.E. Baumana, 2005, 190 p.
5. Kalyanov G.N. Modelirovanie, analiz, reorganizatsiya i avtomatizatsiya biznes-protsessov [Modeling, analysis, reorganization and automation of business processes]. Moscow: Finansy i statistika, 2006, 240 p.
6. Vysochin S.V. Printsipy postroeniya sistem dlya rascheta proizvodstvennykh raspisaniy [Prin-ciples of building systems to calculate production schedules], SAPR i grafika [CAD and Graphics], 2008, No. 9, pp. 57-59.
7. Organizatsiya i planirovanie mashinostroitel'nogo proizvodstva [Organization and planning of engineering production], ed. by Yu.V. Skvortsova, L.A. Nekrasova. Moscow: Vysshaya shko-la, 2003, 470 p.
8. Leung J.Y.T. Handbook of Scheduling // Boca Raton, Florida: Chapman & Hall/CRC, 2004.
9. Gladkov L.A. Gibridnyy geneticheskiy algoritm resheniya zadach operativnogo proizvodstven-nogo planirovaniya [Hybrid genetic algorithm of the decision of problems of operative industrial planning], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2012, No. 7 (132), pp. 35-42.
10. Cohoon J.P., Karro J., Lienig J. Evolutionary Algorithms for the Physical Design of VLSI Circuits. Advances in Evolutionary Computing: Theory and Applications, Ghosh, A., Tsutsui, S. (eds.) Springer Verlag, London, 2003, pp. 683-712.
11. Kureychik V.M., Kureychik V.V., Rodzin S.I. Kontseptsiya evolyutsionnykh vychisleniy, in-spirirovannykh prirodnymi sistemami [Concept evolutionary computation is inspired by natural systems], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2009, No. 4, pp. 16-25.
12. Knysh D.S., Kureychik V.M. Parallel'nye geneticheskie algoritmy: Problemy, obzor i sostoyanie [Parallel genetic algorithms: Problem overview and state], Izvestiya RAN. Teoriya i sistemy upravleniya [Journal of Computer and Systems Sciences International], 2010, No. 4 (93), pp. 72-82.
13. Kureychik V.M. Modifitsirovannye geneticheskie operatory [Modified genetic operators], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2009, No. 12 (101), pp. 7-15.
14. Gromov S.A. Metody adaptivnogo i geneticheskogo poiska v operativnom planirovanii pro-izvodstva [Methods of adaptive and genetic search in operational planning production], Izvestiya vysshikh uchebnykh zavedeniy. Mashinostroenie [Proceedings of Higher Educational Institutions. Маchine Building], 2011, No. 8, pp. 74-80.
15. Gromov S.A. Intellektualizatsiya sistem operativnogo planirovaniya proizvodstva [Intellectual-ization of systems of operative production planning], Sbornik trudov VI Mezhdunarodnoy nauchno-prakticheskoy konferentsii (Kolomna, 16-19 maya 2011 g.) [Proceedings of the VI International scientific-practical conference (Barnaul, 16-19 may 2011)]. Moscow: Fizmatlit, 2011, Vol. 2, pp. 588-598.
16. Gromov S.A., Tarasov V.B. Metody iskusstvennogo intellekta v avtomatizatsii operativnogo planirovaniya [Artificial intelligence methods in the automation of operational planning], Pro-grammnye produkty i sistemy [Software Products and Systems], 2007, No. 4, pp. 89-92.
17. Gromov S.A., Tarasov V.B. Integrirovannye intellektual'nye sistemy operativnogo planirovaniya proizvodstva [Integrated intelligent systems of production planning and scheduling], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2011,
No. 7 (120), pp. 60-67.
18. Gladkov L.A., Gladkova N.V. Novye podkhody k postroeniyu sistem analiza i izvlecheniya znaniy na osnove gibridnykh metodov [New approaches to construction of data mining systems on the basis of hybrid methods], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2010, No. 7 (108), pp. 146-154.
19. Gladkov L.A., Gladkova N.V. Osobennosti ispol'zovaniya nechetkikh geneticheskikh algoritmov dlya resheniya zadach optimizatsii i upravleniya [Features of use of fuzzy genetic algorithms for the decision of problems of optimisation and control], Izvestiya YuFU. Tekhnicheskie nauki [Izvestiya SFedU. Engineering Sciences], 2009, No. 4 (93), pp. 130-136.
20. Gladkov L.A., Gladkova N.V., Leiba S.N. Manufacturing Scheduling Problem Based on Fuzzy Genetic Algorithm, Proceedings of IEEE East-West Design & Test Symposium (EWDTS’2014). Kiev, Ukraine, September 26–29, 2014, pp. 209-213.

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