**Author details**

Gabriela Prelipcean1 and Mircea Boscoianu2

1 Stefan cel Mare University of Suceava, Romania

2 Henri Coanda Air Force Academy of Brasov, Romania

### **References**


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The future developments of the concepts linked to VE (new assessment models based on ability to add real value, changes in the competition nature between firms, new possibilities for integration/ mixing with DSS) should consider the following future directions of re‐ search: the development of VE platforms dedicated for SMEs and startups; the specification of operational characteristics and the analysis of the distributed architectures; the develop‐ ment of the new methods of management, coordination, cooperation and negotiations be‐ tween VEs; special focus on social aspects regarding the development of VEs. Other aspects to cover in future work should take into account: the coordination functionalities such as distributed resource management and scheduling and the new role of negotiation in a VE as a central task in the formation of a VE/ VO but also in the operation and success of these

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**Chapter 6**

**Optimal Control of Integrated Production – Forecasting**

The production planning problem has received much attention, and many sophisticated models and procedures have been developed to deal with this problem. Many other compo‐ nents of production systems have also been taken into account by researchers in so called

In this work, optimal control theory is used to derive the optimal production rate in a manu‐ facturing system presenting the following features: the demand rate during a certain period depends on the demand rate of the previous period (dependent demand), the demand rate depends on the inventory level, items in inventory are subject to deterioration, and the firm can adopt a periodic or a continuous review policy. Also, we are using the fact that the cur‐ rent demand is related to the previous demand in order to integrate the forecasting compo‐ nent into the production planning problem. The forecast of future demand for the products being produced is needed to plan future activities. Forecasting information is an important input in several areas of manufacturing activity. This problem has been considered in the literature. The proposed approach is different from that of other authors which is mainly based on time-series. In [1], the authors deal with the interaction between forecasting and stock control in the case of non-stationary demand. In [2], the authors assume a distribution for the unknown demand, estimate its parameters and replace the unknown demand pa‐ rameters by these estimates in the theoretically correct model. In [3], the authors propose an approach to evaluate the impact of interaction between demand forecasting method and stock control policy on the inventory system performances. In [4], the authors present a sup‐ ply chain management framework based on model predictive control (MPC) and time series forecasting. In [5], the authors consider a data-driven forecasting technique with integrated inventory control for seasonal data and compare it to the traditional Holt-Winters algorithm

> © 2012 Hedjar et al.; licensee InTech. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

© 2012 Hedjar et al.; licensee InTech. This is a paper distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

distribution, and reproduction in any medium, provided the original work is properly cited.

integrated systems, in order to achieve a more effective control over the system.

**System**

**1. Introduction**

R. Hedjar, L. Tadj and C. Abid

Additional information is available at the end of the chapter

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