application of multi-attribute value theory to improve cargo delivery planning in disaster aftermath
Clicks: 11
ID: 252236
2017
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Emerging Content
3.0
/100
11 views
8 readers
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #963 of 1,093 articles by views in journal of power sources
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,093 in total.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
Although many Operational Research models have been applied to disaster response operations, few researchers aim at revealing Decision Makers’ goals or measuring their trade-offs. This article uses a holistic Multi-Criteria Decision Analysis (MCDA) method to elucidate what objectives to pursue and to create appropriate strategies for planning vital items delivery to victims. We propose a framework for applying a Multi-Attribute Value Theory technique and test it with a humanitarian Decision Maker. The resulting mathematical model can be used to evaluate guidelines that make on-field decisions easier, improving (or at least not compromising) their outcomes. Our contribution to the MCDA field includes the documentation of an alternative generation methodology.
| Reference Key |
cavalcanti2017mathematicalapplication
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Luísa Brandão Cavalcanti;André Bergsten Mendes;Hugo Tsugunobu Yoshida Yoshizaki |
| Journal | journal of power sources |
| Year | 2017 |
| DOI |
10.1155/2017/2720470
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.