Technical Note—What’s in a Constraint? On the Ambiguity of Standard Delay Targets

Ambiguities in Average Speed of Answer Targets Staffing problems are often formulated as satisfization problems, in which the cost of servers is minimized subject to quality of service constraints. These constraints are intended to capture customers’ disutility from waiting or, at least, its structure. In “What’s in a constraint? On the ambiguity of standard delay targets,” Soh and Gurvich show that such targets—especially the popular average speed of answer—are ambiguous: they give rise to multiple optimal solutions (prioritization policies), each consistent with different assumptions about how customers value their time. By choosing, among all optimal solutions, the one that minimizes a weighted index of diversion (a generalization of variance for the multiclass queue), a service provider can ensure that its ASA-based staffing and prioritization decisions align with a convex model of customer delay disutility. Nonambiguity can also be enforced by restricting attention to fixed queue ratio priority policies.

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Publication Details

Journal
Operations Research
Published
2025-05-15
DOI
https://doi.org/10.1287/opre.2022.0572
Primary Topic
Advanced Queuing Theory Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

Technical Note—What’s in a Constraint? On the Ambiguity of Standard Delay Targets

Itai Gurvich, Seung Bum Soh
Operations Research
Advanced Queuing Theory Analysis
article

Technical Note—What’s in a Constraint? On the Ambiguity of Standard Delay Targets

Itai Gurvich, Seung Bum Soh
article en

Abstract

Ambiguities in Average Speed of Answer Targets Staffing problems are often formulated as satisfization problems, in which the cost of servers is minimized subject to quality of service constraints. These constraints are intended to capture customers’ disutility from waiting or, at least, its structure. In “What’s in a constraint? On the ambiguity of standard delay targets,” Soh and Gurvich show that such targets—especially the popular average speed of answer—are ambiguous: they give rise to multiple optimal solutions (prioritization policies), each consistent with different assumptions about how customers value their time. By choosing, among all optimal solutions, the one that minimizes a weighted index of diversion (a generalization of variance for the multiclass queue), a service provider can ensure that its ASA-based staffing and prioritization decisions align with a convex model of customer delay disutility. Nonambiguity can also be enforced by restricting attention to fixed queue ratio priority policies.

Operations ResearchVol. 74(1)
Northwestern University (US), Yonsei University (KR)
Openalex Percentile: Top 83%
Advanced Queuing Theory Analysis
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