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Locating on-street loading and unloading spaces by means of mixed integer programming

2018· article· pt· W2801391725 on OpenAlex
Bruno de Athayde Prata, Leise Kelli de Oliveira, Thiago Costa Holanda

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

VenueTransportes · 2018
Typearticle
Languagept
FieldEngineering
TopicUrban and Freight Transport Logistics
Canadian institutionsLockheed Martin (Canada)
FundersConselho Nacional de Desenvolvimento Científico e Tecnológico
KeywordsPhysicsHumanitiesPhilosophy

Abstract

fetched live from OpenAlex

In an urban freight distribution system, determination of the number and location of loading-unloading places is required to regulate loading-unloading operations. This pa­per presents mathematical models for on-street loading-unloading space location based on set-covering problem and p-median problem formulations. The approaches was tested with real data: an area has 160 city blocks and 60 on-street loading-un­loading spaces, in Fortaleza, Brazil. We evaluated four scenarios considering different radius of influence of a loading/unloading spaces. The results indicate this approach has potential for achieving gains in terms of reduction of the distance between the clients and the loading and unloading places: considering that the average distance is a performance indicator (ratio between the total distance and the covered clients), a radius of influence of 400 meters has best relation (0.489) and all clients are covered. The results indicate that the model can be used by planners to allocate loading and unloading areas.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.676
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.023
GPT teacher head0.221
Teacher spread0.197 · 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