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Optimal Control of Service Systems with Heterogeneous Servers and Priority Customers.

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Authors: Chen, David1 (AUTHOR) davidchen@cuhk.edu.cn, Chen, Ruoran2 (AUTHOR) chenrr@swjtu.edu.cn, Wang, Rowan3 (AUTHOR) wangy2021@sustech.edu.cn, Wang, Xuan4 (AUTHOR) xuanwang@ust.hk
Source: Management Science (INFORMS). Aug2025, Vol. 71 Issue 8, p6559-6579. 21p.
Subject Terms: *Optimal control theory, *Markov processes, *Resource allocation, *Heuristic, *Operations research
Abstract: We study service systems with parallel servers and random customer arrivals and focus on the waiting cost of customers. Using a Markov decision process (MDP) modeling approach, we analytically characterize the structures of the optimal dynamic server assignment policies for two important systems, one consisting of multiple homogeneous servers and two classes of customers and the other consisting of two heterogeneous servers and multiple classes of customers. Based on the obtained results, we propose a threshold-type heuristic policy for the generalized system consisting of multiple heterogeneous servers and multiple classes of customers. To design such a heuristic policy, we first develop techniques for the performance evaluation of general threshold-type policies with any given threshold values. We then construct a path to search for the optimal threshold values. We compare the performance of the best threshold-type heuristic policy with that of the optimal policy and show that our proposed heuristic policy is computationally efficient yet generates great performance. To derive additional managerial insights, we compare the system under our threshold-type dynamic server assignment policy with other commonly seen and simple systems, such as the dedicated system and the work-conserving flexible priority system. The clear performance advantage observed from extensive numerical experiments demonstrates the importance and usefulness of dynamic server assignment control for systems serving multiple classes of customer arrivals. Finally, we extend our analysis to incorporate customer-dependent service rates and sojourn-time minimization performance metrics. This paper was accepted by Chung Piaw Teo, optimization. Funding: This work was supported by the Hong Kong Research Grants Council [16500921, 16505819] and the National Natural Science Foundation of China [72201233, 72301222]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01228. [ABSTRACT FROM AUTHOR]
Database: Entrepreneurial Studies Source
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  Data: <searchLink fieldCode="AR" term="%22Chen%2C+David%22">Chen, David</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> davidchen@cuhk.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Chen%2C+Ruoran%22">Chen, Ruoran</searchLink><relatesTo>2</relatesTo> (AUTHOR)<i> chenrr@swjtu.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Rowan%22">Wang, Rowan</searchLink><relatesTo>3</relatesTo> (AUTHOR)<i> wangy2021@sustech.edu.cn</i><br /><searchLink fieldCode="AR" term="%22Wang%2C+Xuan%22">Wang, Xuan</searchLink><relatesTo>4</relatesTo> (AUTHOR)<i> xuanwang@ust.hk</i>
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  Data: <searchLink fieldCode="JN" term="%22Management+Science+%28INFORMS%29%22">Management Science (INFORMS)</searchLink>. Aug2025, Vol. 71 Issue 8, p6559-6579. 21p.
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  Data: *<searchLink fieldCode="DE" term="%22Optimal+control+theory%22">Optimal control theory</searchLink><br />*<searchLink fieldCode="DE" term="%22Markov+processes%22">Markov processes</searchLink><br />*<searchLink fieldCode="DE" term="%22Resource+allocation%22">Resource allocation</searchLink><br />*<searchLink fieldCode="DE" term="%22Heuristic%22">Heuristic</searchLink><br />*<searchLink fieldCode="DE" term="%22Operations+research%22">Operations research</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: We study service systems with parallel servers and random customer arrivals and focus on the waiting cost of customers. Using a Markov decision process (MDP) modeling approach, we analytically characterize the structures of the optimal dynamic server assignment policies for two important systems, one consisting of multiple homogeneous servers and two classes of customers and the other consisting of two heterogeneous servers and multiple classes of customers. Based on the obtained results, we propose a threshold-type heuristic policy for the generalized system consisting of multiple heterogeneous servers and multiple classes of customers. To design such a heuristic policy, we first develop techniques for the performance evaluation of general threshold-type policies with any given threshold values. We then construct a path to search for the optimal threshold values. We compare the performance of the best threshold-type heuristic policy with that of the optimal policy and show that our proposed heuristic policy is computationally efficient yet generates great performance. To derive additional managerial insights, we compare the system under our threshold-type dynamic server assignment policy with other commonly seen and simple systems, such as the dedicated system and the work-conserving flexible priority system. The clear performance advantage observed from extensive numerical experiments demonstrates the importance and usefulness of dynamic server assignment control for systems serving multiple classes of customer arrivals. Finally, we extend our analysis to incorporate customer-dependent service rates and sojourn-time minimization performance metrics. This paper was accepted by Chung Piaw Teo, optimization. Funding: This work was supported by the Hong Kong Research Grants Council [16500921, 16505819] and the National Natural Science Foundation of China [72201233, 72301222]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2023.01228. [ABSTRACT FROM AUTHOR]
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        Value: 10.1287/mnsc.2023.01228
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      – Code: eng
        Text: English
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        PageCount: 21
        StartPage: 6559
    Subjects:
      – SubjectFull: Optimal control theory
        Type: general
      – SubjectFull: Markov processes
        Type: general
      – SubjectFull: Resource allocation
        Type: general
      – SubjectFull: Heuristic
        Type: general
      – SubjectFull: Operations research
        Type: general
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      – TitleFull: Optimal Control of Service Systems with Heterogeneous Servers and Priority Customers.
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            NameFull: Chen, David
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            NameFull: Chen, Ruoran
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            NameFull: Wang, Rowan
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            NameFull: Wang, Xuan
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            – D: 01
              M: 08
              Text: Aug2025
              Type: published
              Y: 2025
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            – TitleFull: Management Science (INFORMS)
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