Simulation Aided Production Planning and Scheduling Using Game Theory Approach

Article Preview

Abstract:

In the paper the concept of using methods and models of the game theory to solve problems in the area of production planning and control is presented. The problems concerning selection of the most favorable routes from given circumstances and for available set of alternative routes in discrete multi-assortment production systems is presented. Considered in this paper the problems related to the allocation of adequate resources to carry out specific production plan of production orders. Combinatorial complexity of those problems is high especially at the operational level. Therefore heuristic or analytical methods are often used in the process of decision support, without indicating the optimum solution. Conducted research in this area are also related to AI methods. The proposed approach in this paper, is based on the game theory in the production planning. The tools of game theory have been used so far mainly in the area of production planning at the levels of strategic and tactical planning. But recently, arises increasingly interest in using game theory in the field of production planning at the operational level. In this case, the player term is replaced with the agent or object term that represents (not the entity or person as it is in the classical approach) production order, production process or package of production orders.

You might also be interested in these eBooks

Info:

Periodical:

Pages:

1450-1455

Citation:

Online since:

November 2015

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2015 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

* - Corresponding Author

[1] P. Argoneto, G. Perrone, P. Renna, G. Lo Nigro, M. Bruccoleri, S. Noto La Diega, Production planning in production networks, Springer-Verlag, London, (2008).

DOI: 10.1007/978-1-84800-058-2

Google Scholar

[2] N. Papakostas, K. Efthymiou, K. Georgoulias, G. Chryssolouris, On the configuration and planning of dynamic manufacturing networks, Logistics Research. 5 3-4 (2012) 105-111.

DOI: 10.1007/s12159-012-0086-9

Google Scholar

[3] S. Saniuk, A. Saniuk, R. Lenort, Formation and planning of virtual production networks (VPN) in metallurgical clusters, Metalurgija. 53 4 (2014) 725-727.

Google Scholar

[4] A. Saniuk, A. Samolejova, A. Saniuk, Benefits and barriers of participation in production networks in a metallurgical cluster - research results, Metalurgija. 54 3 (2015) 567 – 570.

Google Scholar

[5] D. Krenczyk, B. Skolud, Production preparation and order verification systems integration using method based on data transformation and data mapping, Lecture Notes in Artificial Intelligence, Lecture Notes in Computer Science. 6679 (2011) 397-404.

DOI: 10.1007/978-3-642-21222-2_48

Google Scholar

[6] D. Krenczyk, M. Olender, Production planning and control using advanced simulation systems, International Journal of Modern Manufacturing Technologies. VI 2 (2014) 38-43.

Google Scholar

[7] P. Pawlewski, P.E. Dossou, P. Golinska, Using simulation based on agents (ABS) and DES in enterprise integration modelling concepts, Advances in Intelligent and Soft Computing. 157 (2012) 75-83.

DOI: 10.1007/978-3-642-28795-4_9

Google Scholar

[8] D. Krenczyk, B. Skolud, Transient States of Cyclic Production Planning and Control, Applied Mechanics and Materials. 657 (2014) 961-965.

DOI: 10.4028/www.scientific.net/amm.657.961

Google Scholar

[9] K. Kalinowski, C. Grabowik, I. Paprocka, W. Kempa, The model of discrete production scheduling system in UML notation-classes diagrams, Modern Technologies in Industrial Engineering. Advanced Materials Research. 837 (2014) 416-421.

DOI: 10.4028/www.scientific.net/amr.837.416

Google Scholar

[10] L. Xinyu, G. Liang, L. Weidong, Application of game theory based hybrid algorithm for multi-objective integrated process planning and scheduling, Expert Systems with Applications. 39 (2012) 288-297.

DOI: 10.1016/j.eswa.2011.07.019

Google Scholar

[11] W.D. Li, L. Gao, X.Y. Li; Y. Guo, Game theory-based cooperation of process planning and scheduling, in proceedings of the 12th International Conference on Computer Supported Cooperative Work in Design, 2008, pp.841-845.

DOI: 10.1109/cscwd.2008.4537088

Google Scholar

[12] D. He W. Sun, L. Zheng, X. Liao, Scheduling flexible job shop problem subject to machine breakdown with game theory, International Journal of Production Research. 52 13 (2014) 3858-3876.

DOI: 10.1080/00207543.2013.784408

Google Scholar

[13] X. Zheng, J. Zhang, Q. Gao, Application of non-cooperative game theory to multi-objective scheduling problem in the automated manufacturing system, in proceedings of the ACAI International Conference, 2012, pp.554-557.

DOI: 10.1049/cp.2012.1039

Google Scholar