Single routing network model of mobile grocery considering Inventory management with service time dependent demand

Clicks: 3
ID: 286319
2021
Free PDF
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 #744 of 3,757 articles by views in Malay Journal

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 3,757 in total.

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
Sign in to mint
Abstract
Mobile grocery trucks or mobile palengke has become a nationwide initiative to provide people with basic necessities and prime commodities during a time when the country is in lockdown due to the pandemic. However, there is a need for extensive research in order to determine the most efficient way to operate these vehicles since most vehicle routing problems do not integrate certain aspects of a mobile grocery truck such as handling multiple inventory, practicing service time per customer, prioritization of customers and a demand which is dependent on the service time. Studies regarding vehicle routing problems are combined with multiple-product inventory management in order to formulate a mixed-integer nonlinear programming model considering customer prioritization. This model would determine the optimum route to the different customers which would maximize profit given time and capacity constraints. The model would also determine how long the vehicle would operate for a customer given the minimum and maximum service time in order to maximize profit. In addition, it would also identify the optimal amount per product to be brought per trip of the mobile grocery truck given the capacity of the vehicle. In order to analyze how the model would behave given different inputs, different scenarios were applied such as changes in travel time, changes in capacity, change in penalty cost for unserved customers, and exclusion of penalty cost for overtime. From the different scenarios, In addition, removing penalty costs from the equation greatly increases profit as well as reducing the travel time. Changing the capacity of the vehicle does little to the overall profit. The scenario where customer prioritization changes how the system’s decision making behaves. The researchers have also envisioned a sample interface that could be used to utilize the model in an easier way.
Reference Key
persistent_1760658221_68f1832d99752 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Sindac, Charles Joseph V.
Journal Malay Journal
Year 2021
DOI
DOI not found
URL
https://animorepository.dlsu.edu.ph/etdb_induseng/6
Keywords Keywords not found

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.