IDEAS home Printed from https://ideas.repec.org/h/spr/isochp/978-3-030-14302-2_6.html
   My bibliography  Save this book chapter

A Model of an Integrated Analytics Decision Support System for Situational Proactive Control of Recovery Processes in Service-Modularized Supply Chain

In: Handbook of Ripple Effects in the Supply Chain

Author

Listed:
  • Dmitry Ivanov

    (Berlin School of Economics and Law)

  • Boris Sokolov

    (Saint Petersburg Institute for Informatics and Automation of the RAS (SPIIRAS))

Abstract

In the supply chain (SC) recovery process, a disruptive event, planning of the recovery control policy and implementation of this policy are distributed in time and subject to SC structural and parametrical dynamics. In other words, environment, SC structure and its operational parameters may change in the period between the planning of the recovery control policy and its implementation. As such, situational proactive control with combined use of simulation-optimization and analytics is proposed in the paper to improve processes of transition between a disrupted and a restored SC state. Implementation of situational proactive control can reduce investments in robustness and increase resilience by obviating the time traps in transition process control problems. This chapter develops a model of a decision support system for situational proactive control of SC recovery processes based on a combination of optimization and analytics techniques. More specifically, three dynamic models are developed and integrated with each other, i.e. a model of SC material flow control, a model of SC recovery control and a model of SC recovery control adjustment. The given models are developed within a cyber-physical SC framework based on the service modularization approach.

Suggested Citation

  • Dmitry Ivanov & Boris Sokolov, 2019. "A Model of an Integrated Analytics Decision Support System for Situational Proactive Control of Recovery Processes in Service-Modularized Supply Chain," International Series in Operations Research & Management Science, in: Dmitry Ivanov & Alexandre Dolgui & Boris Sokolov (ed.), Handbook of Ripple Effects in the Supply Chain, pages 129-144, Springer.
    • Handle: RePEc:spr:isochp:978-3-030-14302-2_6
    DOI: 10.1007/978-3-030-14302-2_6
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:isochp:978-3-030-14302-2_6. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.