IDEAS home Printed from https://ideas.repec.org/a/spr/binfse/v6y2014i1p17-24.html
   My bibliography  Save this article

Model-Based Decision Support in Manufacturing and Service Networks

Author

Listed:
  • Andreas Fink
  • Natalia Kliewer
  • Dirk Mattfeld
  • Lars Mönch
  • Franz Rothlauf
  • Guido Schryen
  • Leena Suhl
  • Stefan Voß

Abstract

In this paper, we sketch some of the challenges that should be addressed in future research efforts for model-based decision support in manufacturing and service networks. This includes integration issues, taking into account the autonomy of the decision-making entities in face of information asymmetry, the modeling of preferences of the decision makers, efficiently determining robust solutions, i.e. solutions that are insensitive with respect to changes in the problem data, and a reduction of the time needed for model building and usage. The problem solution cycle includes problem analysis, the design of appropriate algorithms and their performance assessment. We are interested in a prototypical integration of the proposed methods within application systems, which can be followed up with field tests of the extended application systems. We argue that the described research agenda requires the interdisciplinary collaboration of business and information systems engineering researchers with colleagues from management science, computer science, and operations research. In addition, we present some exemplifying, illustrative examples of relevant research results. Copyright Springer Fachmedien Wiesbaden 2014

Suggested Citation

  • Andreas Fink & Natalia Kliewer & Dirk Mattfeld & Lars Mönch & Franz Rothlauf & Guido Schryen & Leena Suhl & Stefan Voß, 2014. "Model-Based Decision Support in Manufacturing and Service Networks," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(1), pages 17-24, February.
    • Handle: RePEc:spr:binfse:v:6:y:2014:i:1:p:17-24
    DOI: 10.1007/s12599-013-0310-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s12599-013-0310-4
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s12599-013-0310-4?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Ada Y. Barlatt & Amy Cohn & Oleg Gusikhin & Yakov Fradkin & Rich Davidson & John Batey, 2012. "Ford Motor Company Implements Integrated Planning and Scheduling in a Complex Automotive Manufacturing Environment," Interfaces, INFORMS, vol. 42(5), pages 478-491, October.
    2. Seth A. Fischbein & Edward Yellig, 2011. "Why Is It So Hard to Build and Validate Discrete Event Simulation Models of Manufacturing Facilities?," International Series in Operations Research & Management Science, in: Karl G Kempf & Pınar Keskinocak & Reha Uzsoy (ed.), Planning Production and Inventories in the Extended Enterprise, chapter 0, pages 271-288, Springer.
    3. Gregor Dudek, 2009. "Collaborative Planning in Supply Chains," Springer Books, Springer, number 978-3-540-92176-9, December.
    4. Hasso Plattner & Alexander Zeier, 2011. "In-Memory Data Management," Springer Books, Springer, number 978-3-642-19363-7, December.
    5. Ingmar Steinzen & Vitali Gintner & Leena Suhl & Natalia Kliewer, 2010. "A Time-Space Network Approach for the Integrated Vehicle- and Crew-Scheduling Problem with Multiple Depots," Transportation Science, INFORMS, vol. 44(3), pages 367-382, August.
    6. Goos Kant & Michael Jacks & Corné Aantjes, 2008. "Coca-Cola Enterprises Optimizes Vehicle Routes for Efficient Product Delivery," Interfaces, INFORMS, vol. 38(1), pages 40-50, February.
    7. Alfred Degbotse & Brian T. Denton & Kenneth Fordyce & R. John Milne & Robert Orzell & Chi-Tai Wang, 2013. "IBM Blends Heuristics and Optimization to Plan Its Semiconductor Supply Chain," Interfaces, INFORMS, vol. 43(2), pages 130-141, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhengcai Cao & Lijie Zhou & Biao Hu & Chengran Lin, 2019. "An Adaptive Scheduling Algorithm for Dynamic Jobs for Dealing with the Flexible Job Shop Scheduling Problem," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(3), pages 299-309, June.
    2. Wil M. P. Aalst & Jörg Becker & Martin Bichler & Hans Ulrich Buhl & Jens Dibbern & Ulrich Frank & Ulrich Hasenkamp & Armin Heinzl & Oliver Hinz & Kai-Lung Hui & Matthias Jarke & Dimitris Karagiannis &, 2018. "Views on the Past, Present, and Future of Business and Information Systems Engineering," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 60(6), pages 443-477, December.
    3. Martin Bichler & Ulrich Frank & David Avison & Julien Malaurent & Peter Fettke & Dirk Hovorka & Jan Krämer & Daniel Schnurr & Benjamin Müller & Leena Suhl & Bernhard Thalheim, 2016. "Theories in Business and Information Systems Engineering," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 58(4), pages 291-319, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Tobias Knabke & Sebastian Olbrich, 2018. "Building novel capabilities to enable business intelligence agility: results from a quantitative study," Information Systems and e-Business Management, Springer, vol. 16(3), pages 493-546, August.
    2. Wei Wu & Wanjing Ma & Kejun Long & Heping Zhou & Yi Zhang, 2016. "Designing Sustainable Public Transportation: Integrated Optimization of Bus Speed and Holding Time in a Connected Vehicle Environment," Sustainability, MDPI, vol. 8(11), pages 1-15, November.
    3. Perumal, Shyam S.G. & Lusby, Richard M. & Larsen, Jesper, 2022. "Electric bus planning & scheduling: A review of related problems and methodologies," European Journal of Operational Research, Elsevier, vol. 301(2), pages 395-413.
    4. A A Juan & J Faulin & J Jorba & D Riera & D Masip & B Barrios, 2011. "On the use of Monte Carlo simulation, cache and splitting techniques to improve the Clarke and Wright savings heuristics," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1085-1097, June.
    5. Angel Juan & Javier Faulin & Albert Ferrer & Helena Lourenço & Barry Barrios, 2013. "MIRHA: multi-start biased randomization of heuristics with adaptive local search for solving non-smooth routing problems," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 21(1), pages 109-132, April.
    6. Sebastian Büsch & Volker Nissen & Arndt Wünscher, 0. "Automatic classification of data-warehouse-data for information lifecycle management using machine learning techniques," Information Systems Frontiers, Springer, vol. 0, pages 1-15.
    7. Sistig, Hubert Maximilian & Sauer, Dirk Uwe, 2023. "Metaheuristic for the integrated electric vehicle and crew scheduling problem," Applied Energy, Elsevier, vol. 339(C).
    8. Dorneles, Árton P. & de Araújo, Olinto C.B. & Buriol, Luciana S., 2017. "A column generation approach to high school timetabling modeled as a multicommodity flow problem," European Journal of Operational Research, Elsevier, vol. 256(3), pages 685-695.
    9. Sanjay L. Ahire & John B. Jensen, 2017. "Snider Tire Optimizes Its Customers-Stores-Plants Transportation Network," Interfaces, INFORMS, vol. 47(2), pages 150-162, April.
    10. Perumal, S.S.G. & Dollevoet, T.A.B. & Huisman, D. & Lusby, R.M. & Larsen, J. & Riis, M., 2020. "Solution Approaches for Vehicle and Crew Scheduling with Electric Buses," Econometric Institute Research Papers EI-2020-02, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    11. Calvete, Herminia I. & Galé, Carmen & Iranzo, José A., 2014. "Planning of a decentralized distribution network using bilevel optimization," Omega, Elsevier, vol. 49(C), pages 30-41.
    12. Sven Jäger & Anita Schöbel, 2020. "The blockwise coordinate descent method for integer programs," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 91(2), pages 357-381, April.
    13. Emrah Demir & Tom Van Woensel & Ton de Kok, 2014. "Multidepot Distribution Planning at Logistics Service Provider Nabuurs B.V," Interfaces, INFORMS, vol. 44(6), pages 591-604, December.
    14. Lukas Bach & Twan Dollevoet & Dennis Huisman, 2016. "Integrating Timetabling and Crew Scheduling at a Freight Railway Operator," Transportation Science, INFORMS, vol. 50(3), pages 878-891, August.
    15. Pan Shang & Yu Yao & Liya Yang & Lingyun Meng & Pengli Mo, 2021. "Integrated Model for Timetabling and Circulation Planning on an Urban Rail Transit Line: a Coupled Network-Based Flow Formulation," Networks and Spatial Economics, Springer, vol. 21(2), pages 331-364, June.
    16. Martin Kowalczyk & Peter Buxmann, 2014. "Big Data and Information Processing in Organizational Decision Processes," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 6(5), pages 267-278, October.
    17. Yang, Lin & Gao, Yuan & D’Ariano, Andrea & Xu, Suxiu, 2024. "Integrated optimization of train timetable and train unit circulation for a Y-type urban rail transit system with flexible train composition mode," Omega, Elsevier, vol. 122(C).
    18. Anuj Mittal & Caroline C. Krejci & Teri J. Craven, 2018. "Logistics Best Practices for Regional Food Systems: A Review," Sustainability, MDPI, vol. 10(1), pages 1-44, January.
    19. Amy David & David Farr & Ross Januszyk & Urmila Diwekar, 2015. "USG Uses Stochastic Optimization to Lower Distribution Costs," Interfaces, INFORMS, vol. 45(3), pages 216-227, June.
    20. Kazemi, Ahmad & Ernst, Andreas T. & Krishnamoorthy, Mohan & Le Bodic, Pierre, 2021. "Locomotive fuel management with inline refueling," European Journal of Operational Research, Elsevier, vol. 293(3), pages 1077-1096.

    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:binfse:v:6:y:2014:i:1:p:17-24. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.