Science Journal of Business and Management
Volume 2, Issue 5, October 2014, Pages: 153-162
Received: Oct. 6, 2014;
Accepted: Oct. 28, 2014;
Published: Oct. 30, 2014
Views 2455 Downloads 92
Borislav Gordic, MIRAKO Co., Draskoviceva 57, Zagreb, University NORTH - University Center Varazdin, Department of Logistic, Varazdin, Croatia
In research of a model of production planning and control that can adapt to changes, disturbances and risks a model of adaptable optimization, called discrete corrective dynamizing optimization, was created. The model is created on the basis of dynamic programming to which is added the model of corrective optimization by simulation with the criteria defined in the initial and corrective part of the optimization. The effectiveness of a model of discrete corrective dynamizing programming was tested in relation to three other models of production programming. Testing has shown that the smallest deviations of the product quantities were obtained by applying the model of discrete corrective dynamizing optimization. It was also shown that the difference in the realized profit rate as the optimization criterion in relation to actual results was negligible in all testing conditions-variants. This is also a proof that with the use of corrective optimization a possible optimum can be achieved, with maximum adjustment to changes.
Model of Adaptable Production Planning and Control, Science Journal of Business and Management.
Vol. 2, No. 5,
2014, pp. 153-162.
C.A.Soman; D.P.Van Donk; G.J.C.Gaalman, "Capacitated Planning and Scheduling for Combined Make-to-order and Make-to-stock Production in Food Industry", International Journal of Production Economics, Vol.108, pages 191-199, 2007.
L.C.Hendry; B.G.Kingsman, "Production Planning System and Their Applicability to Make-to-order Companies", European Journal of Operational Research, Vol.40, pages 1-15, 1989.
J.Olhanger; M.Rudberg; J.Vikner, "Long-term Capacity Management: Linking the Perspectives for Manufacturing Strategy and Sales and Operations Planning", International Journal of Production Economics, Vol.69, pages 215-225, 2001.
P. G. Moscoso, J. C. Fransoo, D. Fisher, "An Empirical Study on Reducing Planning Instability in Hierarchical Planning System", Production Planning & Control Journal, 4/2010, pages 413-426
G. C. Kim, M. J. Schniederjans, S. S. Kim, "Simulation Study of Availability Management in a Make-to-order Manufacturing Environment for a Differentiated Order System", Production Planning & Control Journal, 1/2010, pages 47-49
H. Stefansson, P. Jensson, N. Shah, "Procedure for Reducing the Risk of Delayed Deliveries in Make-to-order Production", Production Planning & Control Journal, 4/2009, pages 332-342
J. E. Hernandez, J. Mula, F. J. Ferriols, "A Reference Model for Conceptual Modelling of Production Planning Processes", Production Planning & Control Journal, 8/2008, pages 725-734
M. M. Al Durgham, M. A. Barghash, "A Generalised Framework for Simulation-based Decision Support for Manufacturing", Production Planning & Control Journal, 5/2008, pages 518-534
T. Taskinen, "Improving Change Management Capabilities in Manufacturing: From Theory to Practice", Production Planning & Control Journal, 2/2003, pages 201-211
S. Mestry, P. Damodaran, Chin-Sheng Chen, "A Branch and Price Solution Approach for Order Acceptance and Capacity Planning in Make-to-order Operations", European Journal of Operational Research, Vol.211/2011, pages 480-495
T. Volling, T. S. Spengler, "Modeling and Simulation of Order-driven Planning Policies in Build-to-order Automobile Production", International Journal of Production Economics, Vol.131/2011, pages 183-193
J. Mula, R. Poler; J. P. García-Sabater; F.C. Lario, "Models for Production Planning under Uncertainty: A Review", International Journal of Production Economics, Vol.103/2006, pages 271-285
J. N. D. Gupta, "An Excursion in Scheduling Theory: An Overwiew of Scheduling Research in the Twentieth Century",Production Planning & Control Journal, 2/2002, pages 105-116