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Record W1210901285 · doi:10.1016/j.ifacol.2015.06.305

On-line Supply Chain Scheduling Problem with Capacity Limited Vehicles

2015· article· en· W1210901285 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

VenueIFAC-PapersOnLine · 2015
Typearticle
Languageen
FieldEngineering
TopicScheduling and Optimization Algorithms
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsJob shop schedulingComputer scienceScheduling (production processes)Mathematical optimizationSupply chainCompetitive analysisRobustness (evolution)Operations researchMathematicsComputer networkUpper and lower boundsBusinessRouting (electronic design automation)

Abstract

fetched live from OpenAlex

This paper studies the on-line supply chain scheduling problem for single machine with multiple customers under the constraint of the unlimited number of vehicles but limited vehicle capacity. The customers place their orders on-line, which means that no information of future jobs is known beforehand. The jobs are processed on a single machine and then delivered to the customers by vehicles. Every vehicle can only contain the jobs of the same customer and every batch has the same fixed cost. The objective of the scheduling is to minimize the total makespan and the total delivery cost. Such a problem is called on-line problem. An on-line algorithm for the problem is designed, which is proved to be 2 + 2-competitive. The paper also presents a case study for demonstrating the robustness and efficiency of the algorithm.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.674
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.030
GPT teacher head0.229
Teacher spread0.199 · 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