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Dynamic resource allocation: A flexible and tractable modeling framework

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  • Bertsimas, Dimitris
  • Gupta, Shubham
  • Lulli, Guglielmo

Abstract

This paper presents a binary optimization framework for modeling dynamic resource allocation problems. The framework (a) allows modeling flexibility by incorporating different objective functions, alternative sets of resources and fairness controls; (b) is widely applicable in a variety of problems in transportation, services and engineering; and (c) is tractable, i.e., provides near optimal solutions fast for large-scale instances. To justify these assertions, we model and report encouraging computational results on three widely studied problems – the Air Traffic Flow Management, the Aircraft Maintenance Problems and Job Shop Scheduling. Finally, we provide several polyhedral results that offer insights on its effectiveness.

Suggested Citation

  • Bertsimas, Dimitris & Gupta, Shubham & Lulli, Guglielmo, 2014. "Dynamic resource allocation: A flexible and tractable modeling framework," European Journal of Operational Research, Elsevier, vol. 236(1), pages 14-26.
    • Handle: RePEc:eee:ejores:v:236:y:2014:i:1:p:14-26
    DOI: 10.1016/j.ejor.2013.10.063
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    Cited by:

    1. Seebacher, Gottfried & Winkler, Herwig, 2014. "Evaluating flexibility in discrete manufacturing based on performance and efficiency," International Journal of Production Economics, Elsevier, vol. 153(C), pages 340-351.
    2. Karsu, Özlem & Morton, Alec, 2015. "Inequity averse optimization in operational research," European Journal of Operational Research, Elsevier, vol. 245(2), pages 343-359.
    3. Xia Chen & Yucheng Dong & Ying He, 2024. "Group Risky Choice and Resource Allocation Under Social Comparison Effects," Group Decision and Negotiation, Springer, vol. 33(5), pages 977-1017, October.
    4. Argyris, Nikolaos & Karsu, Özlem & Yavuz, Mirel, 2022. "Fair resource allocation: Using welfare-based dominance constraints," European Journal of Operational Research, Elsevier, vol. 297(2), pages 560-578.
    5. Yong Tian & Bojia Ye & Marc Sáez Estupiñá & Lili Wan, 2018. "Stochastic Simulation Optimization for Route Selection Strategy Based on Flight Delay Cost," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 35(06), pages 1-24, December.
    6. Dinis, Duarte & Barbosa-Póvoa, Ana & Teixeira, Ângelo Palos, 2019. "A supporting framework for maintenance capacity planning and scheduling: Development and application in the aircraft MRO industry," International Journal of Production Economics, Elsevier, vol. 218(C), pages 1-15.
    7. Gülpınar, Nalan & Çanakoğlu, Ethem & Branke, Juergen, 2018. "Heuristics for the stochastic dynamic task-resource allocation problem with retry opportunities," European Journal of Operational Research, Elsevier, vol. 266(1), pages 291-303.
    8. Bertsimas, Dimitris & Griffith, J. Daniel & Gupta, Vishal & Kochenderfer, Mykel J. & Mišić, Velibor V., 2017. "A comparison of Monte Carlo tree search and rolling horizon optimization for large-scale dynamic resource allocation problems," European Journal of Operational Research, Elsevier, vol. 263(2), pages 664-678.
    9. Dimitris Bertsimas & Allison Chang & Velibor V. Mišić & Nishanth Mundru, 2019. "The Airlift Planning Problem," Transportation Science, INFORMS, vol. 53(3), pages 773-773, May.

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