D. Ivanov, B. Sokolov, R. Hartl, A. Pavlov. Structure dynamics control-based integration of aggregate distribution and dynamic transportation planning // 7th IFAC Conference on Manufacturing Modelling, Management, and Control, June 19-21, 2013, Saint Petersburg State University and Saint Petersburg ITMO University, Saint Petersburg, Russia. – IFAC Proceedings Volume # 7, Part# 1, pp. 1920-1925.
D. Ivanov, B. Sokolov, R. Hartl, A. Pavlov. Structure dynamics control-based integration of aggregate distribution and dynamic transportation planning // 7th IFAC Conference on Manufacturing Modelling, Management, and Control, June 19-21, 2013, Saint Petersburg State University and Saint Petersburg ITMO University, Saint Petersburg, Russia. – IFAC Proceedings Volume # 7, Part# 1, pp. 1920-1925.
Abstract
We study dynamic planning decisions of a logistics service provider that in charge of the integrated supply chain (SC) planning. We examine an SC with multiple products, suppliers, transit nodes, and customers. The logistics service provider is responsible for aggregate distribution planning and operative dynamic transportation planning. It is to decide on aggregate distribution flows as well as on the timedependent intensities (i.e., transportation order quantities). These decisions are tightly incorporated but previous research considered them mostly isolated. This is quite naturally since these problems contain data of different detail degree which can be hardly incorporated in only one model. To resolve this problem, we present a hybrid multi-period distribution–transportation model as an optimal control problem blended with linear programming. This contribution has some particular features. First, it extends previous research by elaborating on the dynamic optimal control model. Second, it considers multi-period problem statement with multiple products and alternative transportation channels. Third, we represent the integrated SC planning in terms of structure dynamics control theory in order to take into account execution stage and adaptation. With the results of this study, the dynamic issues in integrated logistics planning in the SC can be addressed, and an intelligent solution to the important problem of SC management has been proposed.