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On‐orbit servicing: a time‐dependent, moving‐target traveling salesman problem

2006· article· en· W2073089651 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

VenueInternational Transactions in Operational Research · 2006
Typearticle
Languageen
FieldComputer Science
TopicOptimization and Search Problems
Canadian institutionsConcordia UniversityUniversité du Québec à Montréal
Fundersnot available
KeywordsSpacecraftSpare partTravelling salesman problemConsumablesComputer scienceOrbit (dynamics)Real-time computingAerospace engineeringSimulationOperations managementAlgorithmEngineeringBusiness

Abstract

fetched live from OpenAlex

Abstract The robotic capability of maintaining and repairing space assets, on‐orbit servicing (OOS), has the potential to change the way spacecraft are designed, manufactured and operated. The most common OOS mission concept envisions an orbital “depot”, where consumables and spare parts for spacecraft will be stored. A “servicing platform”, based at this depot, will be used to service a number of client spacecraft and then return to the depot for resupply. We model OOS as a time‐dependent, moving‐target traveling salesman problem and present an algorithm for minimizing the total amount of energy or time required for OOS operations.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.891
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.042
GPT teacher head0.348
Teacher spread0.306 · 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