Data · dataset · 2025
Multi-agent systems negotiation to deal with dynamic scheduling in disturbed industrial context
Listed in Borealis
It is now accepted that using multi-agent systems improve the reactivity to treat perturbation(s) within flexible manufacturing system.
Description
Intelligent algorithms shall be used to address these perturbation(s) and all smart decision entities within their environment have to continuously negotiate until their common and final goal is achieved. This paper proposes a negotiation-based control approach to deal with variability on a manufacturing system.
It has initially formulated and modeled an environment in which all contributing entities or agents operate, communicate, and interact with each other productively. Then after, simulation and applicability implementation experiments on the basis of full-sized academic experimental platform have been conducted to validate the proposed control approach. Product and resource entities negotiate considering different key performance measures in order to set best priority-based product sequencing.
Read the rest (1 more)
This has been done with expectations that the applicability of the negotiation-based decision-making will be more adaptable to deal with perturbation(s) than another alternative decision-making approach called pure reactive control approach. The result showed that negotiation among the decisional entities has brought significant improvement in reducing makespan and hence conveyed better global performance of a manufacturing system.
Links
Where it is published
- Dataverse dataset page borealisdata.ca/dataset.xhtml?persistentId=doi%3A10.5683%2FSP3%2FATO1SV ↗
landing page · from borealisdata ca
- DOI doi.org/10.5683/sp3/ato1sv ↗
DOI / persistent id · from borealisdata ca
Catalogue records · 1
- Dataverse API borealisdata.ca/api/datasets/:persistentId/?persistentId=doi%3A10.5683%2FSP3%2… ↗
metadata API · from borealisdata ca
Topics
- Stated by source
- Engineering
- From keywords
- Engineering
- Inferred from text
- Manufacturing engineering 69% · Sequencing 75% · Simulation 75%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Borealis | doi:10.5683/SP3/ATO1SV | 10 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:group:4014 | enrichment · borealisdata ca | taxonomy-embedding@1.1.0 | title+keywords+description (69%) |
| concepts[field].dataverse_subject:engineering | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[field].local:field:engineering | mapping · borealisdata ca | connector:borealisdata_ca@1.0.0 | /subjects |
| concepts[method].local:method:simulation | enrichment · borealisdata ca | keyword-concept-rules@1.0.0 | title+description (75%) |
| concepts[modality].local:modality:sequencing | enrichment · borealisdata ca | keyword-concept-rules@1.0.0 | title+description (75%) |
| created_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| description | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /description |
| publication_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| title | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | /name |
| updated_date | source · borealisdata ca | connector:borealisdata_ca@1.0.0 | |
| version_label | source · borealisdata ca | connector:borealisdata_ca@1.0.0 |