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Record W2074972460 · doi:10.1287/trsc.34.3.289.12299

A Bilevel Model and Solution Algorithm for a Freight Tariff-Setting Problem

2000· article· en· W2074972460 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueTransportation Science · 2000
Typearticle
Languageen
FieldComputer Science
TopicOptimization and Variational Analysis
Canadian institutionsPolytechnique MontréalGroup for Research in Decision AnalysisUniversité de Montréal
Fundersnot available
KeywordsTariffBilevel optimizationMathematical optimizationHeuristicRevenueScheduleInteger programmingSet (abstract data type)Integer (computer science)Computer scienceBranch and boundClass (philosophy)Operations researchMathematicsEconomicsOptimization problemFinance

Abstract

fetched live from OpenAlex

We consider a bilevel programming formulation of a freight tariff-setting problem where the leader consists in one among a group of competing carriers and the follower is a shipper. At the upper level, the leader's revenue corresponds to the total tariffs levied, whereas the shipper minimizes its transportation cost, given the tariff schedule set by the leader. We propose for this problem a class of heuristic procedures whose relative efficiencies, on small problem instances, could be validated with respect to optimal solutions obtained from a mixed integer reformulation of the mathematical model. We also present numerical results on large instances that could not be solved to optimality by an exact method.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.750
Threshold uncertainty score0.324

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.249
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it