Locating Urban Consolidation Centers under Shipper Rationality
Bibliographic record
Abstract
An urban consolidation center (UCC) is a logistics facility used to combine deliveries of multiple shippers for reducing freight traffic in dense urban areas. Despite their benefits, such as reducing less-than-truckload deliveries, former applications of UUCs have faced backlash from shippers that were forced to use them even though they did not experience any cost savings. Such failures are often due to an unsuitable location of the UCC and the additional costs of facility operation and maintenance that are unfairly divided between the shippers. This paper introduces shipper rationality to measure the willingness of shippers to use an optimally located UCC. We use a continuum approximation approach to derive the routing costs of the shippers as closed-form expressions. We present three objective functions depending on the preference of the regulatory agency that chooses the location of the UCC, allowing rational shippers to join only if they experience cost savings from the UCC. We discuss influential factors in the optimal location of a UCC, including the customer density of each shipper, the establishment cost of the UCC, and the location of each shipper’s fulfillment center.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".