Public and private optimization at a service facility with approximate information on congestion

Balachandran, Kashi R.; Schaefer, Mark E.

doi:10.1016/0377-2217(80)90006-5

Cited by 27 publications

(4 citation statements)

References 8 publications

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“…aμ 1 μ 2B + bμ 1 μ 2G − μ 1 μ 2G μ 2B c. Using Theorem 1 in Balachandran and Schaefer (1980), there exists a unique equilibrium aggregate traffic rate: λ G = max min(ˆ G , 1 2G (1 − e 1g ) G , 1 2B e 1g G ), 0 .…”

Section: Conclusion and Future Research Directionsmentioning

confidence: 95%

Two-stage security screening strategies in the face of strategic applicants, congestions and screening errors

Song

Zhuang

2015

Ann Oper Res

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In a security screening system, a tighter screening policy not only increases the security level, but also causes congestion for normal people, which may deter their use and decrease the approver's payoff. Adapting to the screening policies, adversary and normal applicants choose whether to enter the screening system. Security managers could use screening policies to deter adversary applicants, but could also lose the benefits of admitting normal applicants when they are deterred, which generates a tradeoff. This paper analyzes the optimal screening policies in an imperfect two-stage screening system with potential screening errors at each stage, balancing security and congestion in the face of strategic normal and adversary applicants. We provide the optimal levels of screening strategies for the approver and the best-response application strategies for each type of applicant. This paper integrates game theory and queueing theory to study the optimal two-stage policies under discriminatory and non-discriminatory screening policies. We extend the basic model to the optimal allocation of total service rate to the assumed two types of applicants at the second stage and find that most of the total service rate are assigned to the service rate for the assumed "Bad" applicants. This paper provides some novel policy insights which may be useful for security screening practices.

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Section: Conclusion and Future Research Directionsmentioning

confidence: 95%

Two-stage security screening strategies in the face of strategic applicants, congestions and screening errors

Song

Zhuang

2015

Ann Oper Res

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“…Note that if is large enough it is only customers of the first (cheapest) class who join and even that may come with some probability. This is another example for a decision model which comes with a class dominance behavior (see Balachandran & Radhakrishnan, 1994;Balachandran & Schaefer, 1979a, 1979b, 1980.…”

Section: The Discrete Casementioning

confidence: 99%

The disadvantage of the Cμ‐rule when customers are strategic

Haviv

2020

Naval Research Logistics

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The question of priorities naturally arises when optimizing service systems with heterogeneous customers. If heterogeneity is with respect to time sensitivity and social welfare is of interest, it is well known that the C -rule is optimal in the sense that customers with high time sensitivity should be prioritized. This, for example, justifies prioritizing more acute patients in public health systems. Using a standard queueing model with strategic customers, we show that, as expected, if admission is centrally controlled, the C -rule remains optimal. However, if admission cannot be controlled, for example, in some public healthcare systems, the C -rule leads to an unusual equilibrium joining behavior. We show that this behavior may result in an inferior social welfare, compared to service disciplines that do not prioritize based on individual time sensitivity level, for example, first-come first-served (FCFS). In particular, the equilibrium strategy under the C -rule is not threshold-based and all customers join with some (type-specific) positive probability. The suboptimality of the C -rule is then demonstrated in a case where the potential arrival rate is high enough such that all the joining probabilities are also less than one. This implies that the resulting social welfare is zero while it is guaranteed to be positive under FCFS.

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“…Using Theorem 1 in (Balachandran and Schaefer, 1980), there exists a unique equilibrium aggregate traffic rate:…”

mentioning

confidence: 99%

N-stage security screening strategies in the face of strategic applicants

Song

Zhuang

2017

Reliability Engineering & System Safety

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From one perspective, tighter security screening has the benefit of deterring adversary passengers and enhancing safety. However, this approach can also produce congestion problems for normal passengers. Adapting to screening policies, both adversary and normal passengers decide their application strategies to the security system to maximize their payoffs, which in turn affects the security agent's payoff. This paper integrates game theory and queueing theory to analyze an N-stage imperfect screening model that considers reject or pass decisions, in which applicants have the chance to be passed or rejected at each stage of the system. An imperfect three-stage screening model is numerically illustrated. Furthermore, the application probabilities, screening probabilities and approver's payoff as functions of the number of screening stages are analyzed. This paper provides some novel insights on screening policies and the optimal number of screening stages which would help security screening policy makers.

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Public and private optimization at a service facility with approximate information on congestion

Cited by 27 publications

References 8 publications

Two-stage security screening strategies in the face of strategic applicants, congestions and screening errors

Two-stage security screening strategies in the face of strategic applicants, congestions and screening errors

The disadvantage of the Cμ‐rule when customers are strategic

N-stage security screening strategies in the face of strategic applicants

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