Muwen Wang, Ghulam Haidar, Faisal Yousafzai, Murad Ul Islam Khan, Waseem Sikandar, Asad Ul Islam Khan
{"title":"Metric dimensions of bicyclic graphs with potential applications in Supply Chain Logistics","authors":"Muwen Wang, Ghulam Haidar, Faisal Yousafzai, Murad Ul Islam Khan, Waseem Sikandar, Asad Ul Islam Khan","doi":"arxiv-2409.02947","DOIUrl":null,"url":null,"abstract":"Metric dimensions and metric basis are graph invariants studied for their use\nin locating and indexing nodes in a graph. It was recently established that for\nbicyclic graph of type-III ($\\Theta $-graphs), the metric dimension is $3$\nonly, when all paths have equal lengths, or when one of the outside path has a\nlength $2$ more than the other two paths. In this article, we refute this claim\nand show that the case where the middle path is $2$ vertices more than the\nother two paths, also has metric dimension $3$. We also determine the metric\ndimension for other values of $p,q,r$ which were omitted in the recent research\ndue to the constraint $p \\leq q \\leq r$. We also propose a graph-based\ntechnique to transform an agricultural supply chain logistics problem into a\nmathematical model, by using metric basis and metric dimensions. We provide a\ntheoretical groundwork which can be used to model and solve these problems\nusing machine learning algorithms.","PeriodicalId":501502,"journal":{"name":"arXiv - MATH - General Mathematics","volume":"40 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - MATH - General Mathematics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.02947","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Metric dimensions and metric basis are graph invariants studied for their use
in locating and indexing nodes in a graph. It was recently established that for
bicyclic graph of type-III ($\Theta $-graphs), the metric dimension is $3$
only, when all paths have equal lengths, or when one of the outside path has a
length $2$ more than the other two paths. In this article, we refute this claim
and show that the case where the middle path is $2$ vertices more than the
other two paths, also has metric dimension $3$. We also determine the metric
dimension for other values of $p,q,r$ which were omitted in the recent research
due to the constraint $p \leq q \leq r$. We also propose a graph-based
technique to transform an agricultural supply chain logistics problem into a
mathematical model, by using metric basis and metric dimensions. We provide a
theoretical groundwork which can be used to model and solve these problems
using machine learning algorithms.