Strategic joining in an M/M/K queue with asynchronous and synchronous multiple vacations
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We study customers’ equilibrium joining strategies in an M/M/K queue with asynchronous and synchronous multiple vacations. Arriving customers face four different information levels, that is, fully observable, almost observable, almost unobservable and fully unobservable cases, and they decide whether to join or balk the system based on their service utility. In this study, we analyse customers’ equilibrium strategies in terms of the social welfare. It is found that the equilibrium social welfare under an asynchronous vacation policy is higher than that under a synchronous vacation policy when the traffic density is low, the opposite relation exists when the traffic density is high. Furthermore, when the traffic density is high enough, the difference between the two vacation policies in terms of social welfare can be negligible. Finally, if all customers follow the equilibrium strategies, compared to the situation with no information provided for customers, the social planner would prefer to reveal the queue length. Such a finding has the managerial implication for waiting line managers who want to maximise the social welfare of customers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it