a novel approach for solving a capacitated location allocation problem

Clicks: 231
ID: 167834
2013
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.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #18 of 24 articles by views in boletin latinoamericano y del caribe de plantas medicinales y aromaticas

Most read Least read

Bar heights use a square-root scale.

Mint this article as an NFT
Not yet minted

Create 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
Location Allocation is one of the most important decision making problems, which attracted many operational researchers during recent decades and many solution procedures are developed so far to cope with this problem. This paper proposes a new graph theory based method to cope with small size capacitated location allocation problems. Additionally, a genetic algorithm is utilized to solve medium and large scale problems. Finally, through some computational experiments, the quality and capability of these algorithms are shown.
Reference Key
rabbani2013internationala Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Masoud Rabbani;Helia Yousefnejad
Journal boletin latinoamericano y del caribe de plantas medicinales y aromaticas
Year 2013
DOI
DOI not found
URL
Keywords

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.