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Record W2074391778 · doi:10.4018/ijfsa.2013070104

Integrating Modified Delphi with Fuzzy AHP for Concrete Production Facility Location Selection

2013· article· en· W2074391778 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 Journal of Fuzzy System Applications · 2013
Typearticle
Languageen
FieldDecision Sciences
TopicMulti-Criteria Decision Making
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsAnalytic hierarchy processFacility location problemSelection (genetic algorithm)Production (economics)Fuzzy logicDelphi methodDelphiComputer scienceOperations researchSensitivity (control systems)Site selectionProcess (computing)EngineeringArtificial intelligenceEconomics

Abstract

fetched live from OpenAlex

Evaluation and selection of concrete production facility location is an important strategic decision making problem for both public and private sector. The multi-dimensional, multi-criteria nature of the concrete production facility location problem limits the usefulness of any particular single objective model. In this study, social, economical, technological, environmental and transportation factors and sub criteria, have been derived to make the optimal concrete production facility location selection decision more realistic and effectual. In this paper, an improved and more appropriate concrete production facility location evaluation and selection model has been developed by integrating Modified Delphi Method (MDM) with Fuzzy Analytic Hierarchy Process (FAHP). A numerical example is presented to show applicability and performance of the proposed methodology followed by a sensitivity analysis to discuss and explain the results.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.830
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
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 integrity0.0000.000
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 head0.093
GPT teacher head0.385
Teacher spread0.292 · 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