Abstract
This article discusses the task of operational planning of one-subject production. Synchronous and asynchronous flows of parts processing are analyzed. The factors influencing the obtaining of an effective solution to the assigned assignment problem in conditions of uncertainty are considered. Comprehensive accounting of the influence of the main factors of operational planning is an urgent problem of improving the management of industrial enterprises. Optimizing the distribution of the totality of work between the machines is of key importance in production planning. This distribution of work must be ensured in such a way that the condition of minimizing costs is met. To solve the problem of assigning operators to certain industrial equipment, a complex of methods of convolution of fuzzy relations was applied. The analysis of the results is presented, which allows us to draw conclusions about the advisability of using the methods of the theory of fuzzy sets for solving production problems.
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References
Lödding, H.: Handbook of Manufacturing Control. Springer, Berlin (2012). https://doi.org/10.1007/978-3-642-24458-2
Mayer, J.H., Winter, R., Mohr, T.: Situational management support systems. Bus. Inf. Syst. Eng. 4, 331–345 (2012)
Ivert, L.K., Jonsson, P.: The potential benefits of advanced planning and scheduling systems in sales and operations planning. Ind. Manage. Data Syst. 110(5), 659–681 (2010)
Grimson, J.A., Pyke, D.F.: Sales and operations planning: an exploratory study and framework. Int. J. Logist. Manage. 18(3), 322–346 (2007)
Kolinski, A., Śliwczyński, B.: IT support of production efficiency analysis in ecological aspect. In: Golinska, P., Kawa, A. (eds.) Technology Management for Sustainable Production and Logistics, pp. 205–219. Springer, Heidelberg (2015). https://doi.org/10.1007/978-3-642-33935-6_11
Olhager, J., Johansson, P.: Linking long-term capacity management for manufacturing and service operations. J. Eng. Tech. Manage. 29(1), 22–33 (2012)
Adamczak, M., Domański, R., Hadaś, Ł, Cyplik, P.: The integration between production-logistics system and its task environment chosen aspects. IFAC-PapersOnline 49(12), 656–661 (2016)
Hentschel, B., et al.: Ranking of integration factors within supply chains of forward and backward types—recommendations from researches. Logforum 11(2), 161–169 (2015)
Berghman, L., Leus, R., Spieksma, F.C.R.: Optimal solutions for a dock assignment problem with trailer transportation. Ann. Oper. Res. 213(1), 3–25 (2011). https://doi.org/10.1007/s10479-011-0971-7
van der Aalst, W., et al.: Process Mining Manifesto. In: Daniel, F., Barkaoui, K., Dustdar, S. (eds.) BPM 2011. LNBIP, vol. 99, pp. 169–194. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-28108-2_19
Khandelwal, A.: A modified approach for assignment method. Int. J. Latest Res. Sci. Technol. 3(2), 136–138 (2014)
Ahmed, A., Ahmad, A.: A new method for finding an optimal solution of assignment problem. Int. J. Mod. Math. Sci. 12(1), 10–15 (2014)
Thiruppathi, A., Iranian, D.: An innovative method for finding optimal solution to assignment problems. IJIRSET 4(8), 7366–7370 (2015)
Ghadle, K.P., Ingle, S.M., Hamoud, A.A.: Optimal solution of fuzzy transshipment problem using generalized hexagonal fuzzy numbers. Int. J. Eng. Technol. (UAE) 7(4.10 Special Issue 10), 558–561 (2018)
Kumar, A., Gupta, A.: Assignment and travelling salesman problems with coefficients as LR fuzzy parameters. Int. J. Appl. Sci. Eng. 10(3), 155–170 (2012)
Kumar, A., Gupta, A., Kaur, A.: Method for solving fully fuzzy assignment problems using triangular fuzzy numbers. Int. J. Comput. Inf. Eng. 3(7), 1889–1892 (2009)
Dehghan, M., Hashemi, B., Ghatee, M.: Computational methods for solving fully fuzzy linear systems. Appl. Math. Comput. 179, 328–343 (2006)
Kofman, A.: Introduction to the Theory of Fuzzy Sets, vol. 1. Academic Press, Amsterdam (1975)
Wasserstein, R., Lazar, N.: The ASA statement on p-values: context, process, and purpose. Am. Stat. 70(2), 129–133 (2016)
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The reported study was funded by the Russian Foundation for Basic Research according to the research project N20-01-00197.
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Kosenko, O., Bozhenyuk, A., Knyazeva, M. (2022). The Task of Optimizing Production Planning with Fuzzy Parameters. In: Kahraman, C., Cebi, S., Cevik Onar, S., Oztaysi, B., Tolga, A.C., Sari, I.U. (eds) Intelligent and Fuzzy Techniques for Emerging Conditions and Digital Transformation. INFUS 2021. Lecture Notes in Networks and Systems, vol 307. Springer, Cham. https://doi.org/10.1007/978-3-030-85626-7_64
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