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Record W4221136472 · doi:10.30829/zero.v5i1.11110

Optimization of Coca-Cola Product Distribution Routes at PT. Graha Prima Mentari Medan With Ant Colony Optimization

2022· article· en· W4221136472 on OpenAlexaff
Pridolin Olin Tarigan, Abil Mansyur

Bibliographic record

VenueZERO Jurnal Sains Matematika dan Terapan · 2022
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicManagement and Optimization Techniques
Canadian institutionsFields Institute for Research in Mathematical Sciences
Fundersnot available
KeywordsBusinessDistribution (mathematics)Business administrationCoca colaAdvertisingOperations managementMarketingMathematicsEngineering

Abstract

fetched live from OpenAlex

<p>PT Graha Prima Mentari is a company engaged in the service sector, namely as the official distributor of Coca-Cola. PT. Graha Prima Mentari has Distribution Centers spread across various cities including those located in the cities of Cirebon, Indramayu, Tasikmalaya, Pekanbaru, Medan, Denpasar, Rembang and others. For branches in the city of Medan PT. Graha Prima Mentari is located at Jalan Gatot Subroto KM 6.7 No. 100 Fields. PT. Graha Prima Mentari has 13 transportation cars that operate from Monday to Saturday and serve 6 areas, namely Medan Barat, Medan Sunggal, Medan Helvetia, Medan Selayang, Medan Tuntungan and Medan Petisah.</p><p>The problem that occurs is that the company has not determined the optimal route which results in additional costs for the distribution of goods. This study aims to minimize the distance by using the ant colony optimization method. The result obtained is that the distribution distance is reduced by 52 km from the previous distance of 93.1 km to 41.1 km and saves distribution costs of Rp.49,000.</p>

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
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 score0.647
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.201
Teacher spread0.193 · 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 designSimulation or modeling
Domainnot available
GenreEmpirical

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
Published2022
Admission routes1
Has abstractyes

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