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The Sum Of Absolute Differences On A Network: Algorithm And Comparison With Other Equality Measures

2003· article· en· W2399990458 on OpenAlex
M. C. López-de-los-Mozos, Juan A. Mesa

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.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueINFOR Information Systems and Operational Research · 2003
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFacility Location and Emergency Management
Canadian institutionsnot available
Fundersnot available
KeywordsCombinatoricsMeasure (data warehouse)HumanitiesMathematicsAlgorithmComputer sciencePhysicsPhilosophyData mining

Abstract

fetched live from OpenAlex

AbstractIn this work, we address a double objective. In the first place, we study the problem of locating a single facility on a network N(V,E) which minimizes the sum of absolute differences between all pairs of weighted travel distances from the users to the facility, and we propose an O (|E|V|2log |V|)) algorithm for solving it. Likewise, we present a computational experience in which we compare the behavior of several equality measures by means of the placement of their respective optimal locations. To this end we define a measure of relative proximity between two optima, and we analyze the results obtained by considering several setting models of the network.RésuméCe travail poursuit un double objectif: nous étudions d’abord le problème concernant la localisation d’une facilité sur un réseau qui minimise l’addition des différences absolues entre toutes les paires de distances pondérées des usagers au facilité, et nous proposons une algorithme de temps O(|E||V|2log |V|) pour le résoudre. Nous présentons également une expérience computationnelle où nous comparons le comportement de plusieurs mesures d’égalité, au moyen de l’emplacement des respectives localisations optimales. Pour ce faire, nous définissons une mesure de proximité relative entre deux optima et nous analysons les résultats obtenus pour plusieurs modèles de réseaux.Key words:: FacilityLocationNetworksEquality criterionMots-clés:: FacilitéLocalisationRéseauCritère d’égalité Additional informationNotes on contributorsMa Cruz López-De-Los-MozosMa Cruz López-de-los-Mozos is a Lecturer of the University School in the Applied Mathematics I Department at the University of Sevilla, Spain. She received a Master of Science at the Complutense University of Madrid and a PhD in Mathematics at the University of Sevilla. Her main research interest is location analysis with equality measures. She has published in the European Journal of Operational Research, the Journal of the Operational Research Society, RAIRO Operations Research and Studies in Locational Analysis.Juan A. MesaJuan A. Mesa is a Professor in the Applied Mathematics Department II at the University of Sevilla. He holds a Master of Science and a PhD in Mathematics from the University of Sevilla. He has published in Computers & Operations Research, Discrete Applied Mathematics, European Journal of Operational Research, International Journal of Industrial Engineering, the Journal of Advanced Transportation, the Journal of the Operational Research Society and Studies in Locational Analysis, among others. His research interests include location of extensive facilities both in networks and continuous spaces, location of facilities with undesirable effects and metro network design. He has been the main researcher of several projects and, in particular, he is the coordinator of the Spanish Thematic Network on Locational Analysis and its Applications.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.965
Threshold uncertainty score0.680

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
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 head0.124
GPT teacher head0.333
Teacher spread0.209 · 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