IDEAS home Printed from https://ideas.repec.org/a/inm/orinte/v48y2018i5p467-483.html
   My bibliography  Save this article

The Inmate Assignment and Scheduling Problem and Its Application in the Pennsylvania Department of Corrections

Author

Listed:
  • Mohammad Shahabsafa

    (Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, Pennsylvania 18015)

  • Tamás Terlaky

    (Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, Pennsylvania 18015)

  • Naga Venkata Chaitanya Gudapati

    (Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, Pennsylvania 18015)

  • Anshul Sharma

    (Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, Pennsylvania 18015)

  • George R. Wilson

    (Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, Pennsylvania 18015)

  • Louis J. Plebani

    (Department of Industrial and Systems Engineering, Lehigh University, Bethlehem, Pennsylvania 18015)

  • Kristofer B. Bucklen

    (Pennsylvania Department of Corrections, Mechanicsburg, Pennsylvania 17050)

Abstract

The inmate assignment project, in close collaboration with the Pennsylvania Department of Corrections (PADoC), took five years from start to successful implementation. In this project we developed the Inmate Assignment Decision Support System (IADSS), for which the primary goal is simultaneous and system-wide optimal assignment of inmates to correctional institutions (CIs). We develop a novel hierarchical, multiobjective mixed-integer linear optimization (MILO) model, which accurately describes the inmate assignment problem (IAP). The IAP is the mathematical optimization formulation of the problem every correctional system faces, which is to assign inmates to CIs and schedule their programs, while considering all legal restrictions and best practice constraints. By using actual inmate data sets from the PADoC, we also demonstrate that the MILO model can be solved efficiently. IADSS enables the PADoC to significantly reduce the inmate population management costs and enhance public safety and security of the CIs. To the best of our knowledge this is the first time that operations research methodologies have been incorporated into the routine business practice of a correctional system and used to optimize its operations. This successful project opens a rich and untouched area for the application of operations research and optimization methodology. The new model and methodology can be utilized for the assignment of inmates in any correctional system.

Suggested Citation

  • Mohammad Shahabsafa & Tamás Terlaky & Naga Venkata Chaitanya Gudapati & Anshul Sharma & George R. Wilson & Louis J. Plebani & Kristofer B. Bucklen, 2018. "The Inmate Assignment and Scheduling Problem and Its Application in the Pennsylvania Department of Corrections," Interfaces, INFORMS, vol. 48(5), pages 467-483, October.
    • Handle: RePEc:inm:orinte:v:48:y:2018:i:5:p:467-483
    DOI: 10.1287/inte.2018.0962
    as

    Download full text from publisher

    File URL: https://doi.org/10.1287/inte.2018.0962
    Download Restriction: no
    File URL: https://libkey.io/10.1287/inte.2018.0962?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
    ---><---

    References listed on IDEAS

    as
    1. Alberto Caprara & Paolo Toth & Daniele Vigo & Matteo Fischetti, 1998. "Modeling and Solving the Crew Rostering Problem," Operations Research, INFORMS, vol. 46(6), pages 820-830, December.
    2. H. W. Kuhn, 1955. "The Hungarian method for the assignment problem," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 2(1‐2), pages 83-97, March.
    3. J. P. Arabeyre & J. Fearnley & F. C. Steiger & W. Teather, 1969. "The Airline Crew Scheduling Problem: A Survey," Transportation Science, INFORMS, vol. 3(2), pages 140-163, May.
    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. Najmaddin Akhundov & Nail Tahirov & Christoph H. Glock, 2022. "Optimal Scheduling of Waitstaff with Different Experience Levels at a Restaurant Chain," Interfaces, INFORMS, vol. 52(4), pages 324-343, July.

    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. Cynthia Barnhart & Peter Belobaba & Amedeo R. Odoni, 2003. "Applications of Operations Research in the Air Transport Industry," Transportation Science, INFORMS, vol. 37(4), pages 368-391, November.
    2. Maenhout, Broos & Vanhoucke, Mario, 2010. "A hybrid scatter search heuristic for personalized crew rostering in the airline industry," European Journal of Operational Research, Elsevier, vol. 206(1), pages 155-167, October.
    3. Huili Zhang & Rui Du & Kelin Luo & Weitian Tong, 2022. "Learn from history for online bipartite matching," Journal of Combinatorial Optimization, Springer, vol. 44(5), pages 3611-3640, December.
    4. Thomas L. Magnanti, 2021. "Optimization: From Its Inception," Management Science, INFORMS, vol. 67(9), pages 5349-5363, September.
    5. Weiqiang Shen & Chuanlin Zhang & Xiaona Zhang & Jinglun Shi, 2019. "A fully distributed deployment algorithm for underwater strong k-barrier coverage using mobile sensors," International Journal of Distributed Sensor Networks, , vol. 15(4), pages 15501477198, April.
    6. Chunmei Liu & Legand Burge & Ajoni Blake, 2010. "Algorithms and time complexity of the request-service problem," Journal of Combinatorial Optimization, Springer, vol. 20(2), pages 180-193, August.
    7. repec:wsi:jeapmx:v:20:y:2018:i:04:n:s021919891850007x is not listed on IDEAS
    8. Xiong, Yifan & Li, Ziyan, 2022. "Staffing problems with local network externalities," Economics Letters, Elsevier, vol. 212(C).
    9. M Lezaun & G Pérez & E Sáinz de la Maza, 2010. "Staff rostering for the station personnel of a railway company," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(7), pages 1104-1111, July.
    10. András Frank, 2005. "On Kuhn's Hungarian Method—A tribute from Hungary," Naval Research Logistics (NRL), John Wiley & Sons, vol. 52(1), pages 2-5, February.
    11. Ramjattan, Reshawn & Hosein, Nicholas & Hosein, Patrick & Knoesen, Andre, 2022. "Dynamic group formation in an online social network," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    12. Amit Kumar & Anila Gupta, 2013. "Mehar’s methods for fuzzy assignment problems with restrictions," Fuzzy Information and Engineering, Springer, vol. 5(1), pages 27-44, March.
    13. Fišar, Miloš & Greiner, Ben & Huber, Christoph & Katok, Elena & Ozkes, Ali & Management Science Reproducibility Collaboration, 2023. "Reproducibility in Management Science," Department for Strategy and Innovation Working Paper Series 03/2023, WU Vienna University of Economics and Business.
    14. Viktor Tihanyi & András Rövid & Viktor Remeli & Zsolt Vincze & Mihály Csonthó & Zsombor Pethő & Mátyás Szalai & Balázs Varga & Aws Khalil & Zsolt Szalay, 2021. "Towards Cooperative Perception Services for ITS: Digital Twin in the Automotive Edge Cloud," Energies, MDPI, vol. 14(18), pages 1-26, September.
    15. Tsoukias, Alexis, 2008. "From decision theory to decision aiding methodology," European Journal of Operational Research, Elsevier, vol. 187(1), pages 138-161, May.
    16. Sebastián Genta & Juan Muñoz, 2007. "On assigning drivers for a home-delivery system on a performance basis," Annals of Operations Research, Springer, vol. 155(1), pages 107-117, November.
    17. Gharehgozli, Amir & Zaerpour, Nima, 2020. "Robot scheduling for pod retrieval in a robotic mobile fulfillment system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    18. Haase, Knut, 1999. "Retail business staff scheduling under complex labor relations," Manuskripte aus den Instituten für Betriebswirtschaftslehre der Universität Kiel 511, Christian-Albrechts-Universität zu Kiel, Institut für Betriebswirtschaftslehre.
    19. Nisse, Nicolas & Salch, Alexandre & Weber, Valentin, 2023. "Recovery of disrupted airline operations using k-maximum matching in graphs," European Journal of Operational Research, Elsevier, vol. 309(3), pages 1061-1072.
    20. Parvin Ahmadi & Iman Gholampour & Mahmoud Tabandeh, 2018. "Cluster-based sparse topical coding for topic mining and document clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 12(3), pages 537-558, September.
    21. Reuven Rubinstein, 2013. "Stochastic Enumeration Method for Counting NP-Hard Problems," Methodology and Computing in Applied Probability, Springer, vol. 15(2), pages 249-291, June.

    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:inm:orinte:v:48:y:2018:i:5:p:467-483. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.