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Record W4413286806 · doi:10.3934/math.2025836

A simplified approach to solve hesitant fuzzy linear programming problem with hesitant decision variables and right-hand-side values

2025· article· en· W4413286806 on OpenAlexaff
Raina Ahuja, Meraj Ali Khan, Parul Tomar, Amit Kumar, S. S. Appadoo, Ibrahim Al-Dayel

Bibliographic record

VenueAIMS Mathematics · 2025
Typearticle
Languageen
FieldDecision Sciences
TopicMulti-Criteria Decision Making
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsLinear programmingFuzzy logicComputer scienceOperations researchMathematical optimizationMathematicsArtificial intelligence

Abstract

fetched live from OpenAlex

An approach (a generalization of the classical simplex algorithm) is proposed to solve hesitant fuzzy linear programming problems (HFLPPs). In this paper, we pointed out that much computational effort is required to solve HFLPPs by the existing approach. Moreover, to reduce the computational efforts, an alternative approach is proposed to solve HFLPPs. Furthermore, some other advantages of the proposed alternative approach (PrAlApp) over the existing approach are discussed. Finally, an existing HFLPP is solved by the PrAlApp.

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)0.005
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.491
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0010.001
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 head0.064
GPT teacher head0.361
Teacher spread0.297 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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