Importance Defense industry is a critical area; therefore, defense contractors require greater attention. Nowadays, their development is one of top priorities, and there are many long-term projects in this sphere. The article addresses the actions to be taken in the near future to improve the efficiency of defense enterprises using available resources. Objectives We attempt to develop a conceptual model to optimize the production plan using the ideas of multi-agent simulation that takes into account the characteristics of the target group. Methods We analyze the current situation in the defense industry. Based on the analysis, we formulate basic requirements for the planning model under development. We also formulate the concept of production planning, using the latest developments in the field of multi-agent simulation. Results The article presents a conceptual model of the multi-agent planning system, which is capable to function in severe environment, including critical capacity utilization, and may respond to changes in the shortest time possible. Conclusions and Relevance The developed concept takes into account the specifics of technologically complex production of the military-industrial complex; therefore, if applied, it may improve the productive efficiency at these enterprises.
Bat'kovskii A.M., Fomina A.V. Neobkhodimost' i zadachi modernizatsii oboronno-promyshlennogo kompleksa Rossii [The need for and objectives of modernization of the Russian military-industrial complex]. Elektronnaya promyshlennost' = Electronic Industry, 2014, no. 4, pp. 3–15.
Avdonin B.N., Khrustalev E.Yu. Metodologiya organizatsionno-ekonomicheskogo razvitiya naukoemkikh proizvodstv [A methodology of organizational and economic development of high technology industries]. Moscow, Nauka Publ., 2010, 367 p.
Lopatkin R.V., Zhilkin O.N. Aircraft Maintenance Repair and Overhaul Market in Russia – Challenges and Opportunities of the High-Tech Industry in Russia. In: Globalizing Businesses for the Next Century: Visualizing and Developing Contemporary Approaches to Harness Future Opportunities. New York, Global Business and Technology Association, 2013, pp. 1316–1322.
Oladov N.A., Piterkin S.V., Isaev D.V. Tochno vovremya dlya Rossii. Praktika primeneniya ERP-sistem [Just in time for Russia. Practical application of ERP-systems]. Moscow, Al'pina Pablisher Publ., 2010, 368 p.
Bat'kovskii A.M., Bat'kovskii M.A., Gordeiko S.V., Merzlyakova A.P. Otsenka ekonomicheskoi ustoichivosti predpriyatii oboronno-promyshlennogo kompleksa [Assessing the economic sustainability of the military-industrial complex enterprises]. Audit i finansovyi analiz = Audit and Financial Analysis, 2011, no. 6, pp. 120–126.
Berger G. Ten Ways MRP Can Defeat You. Conference Proceedings. APICS, 1987, pp. 240–243.
Bat'kovskii A.M., Fomina A.V., Khrustalev E.Yu. Upravlenie riskom pri sozdanii produktsii voennogo naznacheniya [Risk management in military products manufacture]. Voprosy radioelektroniki. Ser. Obshchetekhnicheskaya = Issues of Radioelectronics, General Technical Issues Series, 2014, no. 3, pp. 177–190.
Askin R.G., Chen J. Dynamic task assignment for throughput maximization with worksharing. European Journal of Operational Research, 2006, no. 168, pp. 853–869.
Kis T. Job-shop scheduling with processing alternatives. European Journal of Operational Research, 2003, no. 151, pp. 307–332.
Becker C., Scholl A. A survey on problems and methods in generalized assembly line balancing. European Journal of Operational Research, 2006, no. 168, pp. 694–715.
Spearman M., Woodruff D., Hopp W. CONWIP: a pull alternative to kanban. International Journal of Production Research, 1990, no. 28, pp. 879–894.
Bonvik A.M., Couch C.E., Gershwin S.B. A comparison of production line-control mechanisms. International Journal of Production Research, 1997, vol. 35, no. 3, pp. 789–804.
Goldratt E.M., Cox J. Tsel': protsess nepreryvnogo sovershenstvovaniya [The Goal: A Process of Ongoing Improvement]. Minsk, Popurri Publ., 2009, 400 p.
Blackstone J.H.Jr., Cox J.F.III, Schleier J.G.Jr. A tutorial on project management from a theory of constraints perspective. International Journal of Production Research, 2009, no. 47 (24), pp. 7029–7046.
Panurak H.V.D. A practitioners’ review of industrial agent applications. Autonomous Agents and Multi-Agent Systems, 2000, no. 3, pp. 389–407.
Pham D.T., Eldukhri E.E., Soroka A.J. Intelligent Production Machine and Systems. Proceedings of the 2nd Virtual International Conference on Intelligent Production Machines and Systems. Oxford, Elsevier Science, 2006, 671 p.
Bagrinovskii K.A., Matyushok V.M. Ekonomiko-matematicheskie metody i modeli [Economic and mathematical methods and models]. Moscow, Peoples’ Friendship University of Russia Publ., 1999, 183 p.
Parkes D.C., Ungar L.H. Iterative Combinatorial Auctions: Theory and Practice. Proceedings of the 17th National Conference on Artificial Intelligence. American Association for Artificial Intelligence, 2000, pp. 74–81.
Azaron A., Fynes B., Modarres M. Due date assignment in repetitive projects. International Journal of Production Economics, 2011, no. 129, pp. 79–85.
Wong T.N., Leung C.W., Mak K.L., Fung R.Y.K. Dynamic shopfloor scheduling in multi-agent manufacturing systems. Expert Systems with Applications, 2006, no. 31, pp. 486–494.
Pendharkar P.C. A computational study on design and performance issues of multi-agent intelligent systems for dynamic scheduling environments. Expert Systems with Applications, 1999, no. 16, pp. 121–133.
