multiobjective dynamic vehicle routing problem and time seed based solution using particle swarm optimization
Clicks: 134
ID: 211195
2015
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
Popular Article
30.0
/100
134 views
20 readers
AI Quality Assessment
Not analyzed
Readership in this journal
PopularRanked #145 of 205 articles by views in BMC infectious diseases
Most read
Least read
Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 205 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
A multiobjective dynamic vehicle routing problem (M-DVRP) has been identified and a time seed based solution using particle swarm optimization (TS-PSO) for M-DVRP has been proposed. M-DVRP considers five objectives, namely, geographical ranking of the request, customer ranking, service time, expected reachability time, and satisfaction level of the customers. The multiobjective function of M-DVRP has four components, namely, number of vehicles, expected reachability time, and profit and satisfaction level. Three constraints of the objective function are vehicle, capacity, and reachability. In TS-PSO, first of all, the problem is partitioned into smaller size DVRPs. Secondly, the time horizon of each smaller size DVRP is divided into time seeds and the problem is solved in each time seed using particle swarm optimization. The proposed solution has been simulated in ns-2 considering real road network of New Delhi, India, and results are compared with those obtained from genetic algorithm (GA) simulations. The comparison confirms that TS-PSO optimizes the multiobjective function of the identified problem better than what is offered by GA solution.
| Reference Key |
kaiwartya2015journalmultiobjective
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Omprakash Kaiwartya;Sushil Kumar;D. K. Lobiyal;Pawan Kumar Tiwari;Abdul Hanan Abdullah;Ahmed Nazar Hassan |
| Journal | BMC infectious diseases |
| Year | 2015 |
| DOI |
10.1155/2015/189832
|
| 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.