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Main Authors: Sanim, Md. Musfiqur Rahman, Saira, Safrunnesa, Ahsan, Fatin Faiaz, Bardhan, Rajon, Ferdous, S. M.
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2403.11811
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author Sanim, Md. Musfiqur Rahman
Saira, Safrunnesa
Ahsan, Fatin Faiaz
Bardhan, Rajon
Ferdous, S. M.
author_facet Sanim, Md. Musfiqur Rahman
Saira, Safrunnesa
Ahsan, Fatin Faiaz
Bardhan, Rajon
Ferdous, S. M.
contents Given a n points in two dimensional space, a Manhattan Network G is a network that connects all n points with either horizontal or vertical edges, with the property that for any two point in G should be connected by a Manhattan path and distance between this two points is equal to Manhattan Distance. The Minimum Manhattan Network problem is to find a Manhattan network with minimum network length, i.e., summation of all line segment in network should be minimize. In this paper, we proposed a 2-approximation algorithm with time complexity O(|E|lgN) where |E| is the number of edges and N is the number of nodes. Using randomly generated datasets, we compare our result with the optimal one.
format Preprint
id arxiv_https___arxiv_org_abs_2403_11811
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Simple 2-Approximation Algorithm For Minimum Manhattan Network Problem
Sanim, Md. Musfiqur Rahman
Saira, Safrunnesa
Ahsan, Fatin Faiaz
Bardhan, Rajon
Ferdous, S. M.
Computational Geometry
Computer Science and Game Theory
Given a n points in two dimensional space, a Manhattan Network G is a network that connects all n points with either horizontal or vertical edges, with the property that for any two point in G should be connected by a Manhattan path and distance between this two points is equal to Manhattan Distance. The Minimum Manhattan Network problem is to find a Manhattan network with minimum network length, i.e., summation of all line segment in network should be minimize. In this paper, we proposed a 2-approximation algorithm with time complexity O(|E|lgN) where |E| is the number of edges and N is the number of nodes. Using randomly generated datasets, we compare our result with the optimal one.
title A Simple 2-Approximation Algorithm For Minimum Manhattan Network Problem
topic Computational Geometry
Computer Science and Game Theory
url https://arxiv.org/abs/2403.11811