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Record W2227332211 · doi:10.3138/infor.52.4.185

Valid Inequalities and Separation Algorithms for the Set Partitioning Problem

2014· article· en· W2227332211 on OpenAlexafffundvenue
Mounira Groiez, Guy Desaulniers, Odile Marcotte

Bibliographic record

VenueINFOR Information Systems and Operational Research · 2014
Typearticle
Languageen
FieldComputer Science
TopicAdvanced Graph Theory Research
Canadian institutionsUniversité du Québec à MontréalPolytechnique MontréalGroup for Research in Decision Analysis
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSolverSet (abstract data type)CliqueRank (graph theory)Mathematical optimizationComputer scienceInequalityAlgorithmMathematicsCombinatoricsProgramming language

Abstract

fetched live from OpenAlex

In this article we investigate some strategies for solving set partitioning problems (SPP), in particular the gains in computational efficiency that can be obtained by introducing cutting planes based on some rank-1 Chvátal-Gomory inequalities and clique inequalities. We show that for many instances of the SPP, the introduction of some of these cutting planes into the standard SPP model enables a commercial solver such as CPLEX to compute optimal solutions more efficiently.

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.

How this classification was reachedexpand

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.983
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.004
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 head0.131
GPT teacher head0.418
Teacher spread0.288 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designTheoretical or conceptual
Domainnot available
GenreMethods

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".

Quick stats

Citations2
Published2014
Admission routes3
Has abstractyes

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