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An optimal-control based integrated model of supply chain

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  • Ivanov, Dmitry
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    Abstract

    Problems of supply chain scheduling are challenged by high complexity, combination of continuous and discrete processes, integrated production and transportation operations as well as dynamics and resulting requirements for adaptability and stability analysis. A possibility to address the above-named issues opens modern control theory and optimal program control in particular. Based on a combination of fundamental results of modern optimal program control theory and operations research, an original approach to supply chain scheduling is developed in order to answer the challenges of complexity, dynamics, uncertainty, and adaptivity. Supply chain schedule generation is represented as an optimal program control problem in combination with mathematical programming and interpreted as a dynamic process of operations control within an adaptive framework. The calculation procedure is based on applying Pontryagin’s maximum principle and the resulting essential reduction of problem dimensionality that is under solution at each instant of time. With the developed model, important categories of supply chain analysis such as stability and adaptability can be taken into consideration. Besides, the dimensionality of operations research-based problems can be relieved with the help of distributing model elements between an operations research (static aspects) and a control (dynamic aspects) model. In addition, operations control and flow control models are integrated and applicable for both discrete and continuous processes.

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    File URL: http://dspace.gsom.spbu.ru/jspui/handle/123456789/176
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    Bibliographic Info

    Paper provided by Graduate School of Management, St. Petersburg State University in its series Working Papers with number 176.

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    Date of creation: 2010
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    Handle: RePEc:sps:wpaper:176

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    Keywords: supply chain; model of supply chain scheduling; optimal program control theory; Pontryagin’s maximum principle; operations research model;

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