scholarly journals Balanced Labeling and Balance Index Set of One Point Union of Two Complete Graphs

2012 ◽  
Vol 52 (13) ◽  
pp. 1-5
Author(s):  
Pradeep G.Bhat ◽  
Devadas Nayak C
Keyword(s):  
Complete Graphs ◽  
Index Set ◽  
Balance Index

3-VERTEX FULL BALANCE INDEX SET OF GRAPHS

2020 ◽  
Vol 9 (6) ◽  
pp. 3247-3264
Author(s):  
N. C. Devadas ◽  
H. J. Gowtham ◽  
S. D'Souza ◽  
P. G. Bhat
Keyword(s):  
Index Set ◽  
Balance Index

scholarly journals ON VERTEX BALANCE INDEX SET OF SOME SNAKE GRAPHS

2021 ◽  
Vol 28 (2) ◽  
pp. 253-265
Author(s):  
Francis A. Manico ◽  
Ariel C. Pedrano
Keyword(s):  
Index Set ◽  
Balance Index

On Edge-Balance Index Sets of a Nested Graph with Infinite Paths and Power Circles

2013 ◽  
Vol 340 ◽  
pp. 561-566
Author(s):  
Hong Juan Tian ◽  
Yu Ge Zheng
Keyword(s):  
Index Set ◽  
Index Sets ◽  
Class Graph ◽  
Balance Index

We generalize the concept of edge-balanced labeling to the concept of edge-balance index set of graphs. In this article, we define all class of the nested graph with infinite for the integer and investigate the edge-balance index set of a class graph. In particular, we completely determine the edge-balance index sets of the class graph for the integer and solve formula proof and graphic tectonic methods.

scholarly journals On $1$-ddge balance index set of $C_n\times P_4$, $DSC$ and $RC$

2021 ◽  
Vol 9 (1) ◽  
pp. 204-207
Author(s):  
H . N. Shwetha ◽  
B. Shanmukha ◽  
A.S. Shrikanth ◽  
A.R. Nagalakshmi
Keyword(s):  
Index Set ◽  
Balance Index

Sensitivity Analysis and Selection of Check Index of Signal Intersection Simulation Model Based on VISSIM

2019 ◽  
Vol 2 (5) ◽  
Author(s):  
Mengda Zhang ◽  
Chenjing Zhou ◽  
Tian-tian Zhang ◽  
Yan Han
Keyword(s):  
Sensitivity Analysis ◽  
Simulation Model ◽  
Optimal Process ◽  
Parameter Calibration ◽  
Index Set ◽  
The Core ◽  
Core Module ◽  
Simulation Parameter ◽  
Simulation Parameters ◽  
Selection Of

Selecting check index quantitatively is the core of the calibration of micro traffic simulation parameters at signal intersection. Five indexes in the node (intersection) module of VISSIM were selected as the check index set. Twelve simulation parameters in the core module were selected as the simulation parameters set. Optimal process of parameter calibration was proposed and model of the intersection of Huangcun west street and Xinghua street in Beijing was built in VISSIM to verify it. The sensitivity analysis between each check index and simulation parameter in their own set was conducted respectively. Sensitive parameter sets of different check indices were obtained and compared. The results show that different indexes have different size of set, and average vehicle delay's is maximum, so it's necessary to select index quantitatively. The results can provide references for scientific selection of the check indexes and improve the study efficiency of parameter calibration.

Roulette Wheel Selection based Heuristic Algorithm for the Orienteering Problem

2014 ◽  
Vol 13 (1) ◽  
pp. 4127-4145
Author(s):  
Madhushi Verma ◽  
Mukul Gupta ◽  
Bijeeta Pal ◽  
Prof. K. K. Shukla
Keyword(s):  
Triangle Inequality ◽  
Time Budget ◽  
Control Point ◽  
Hamiltonian Path ◽  
Real Life ◽  
Tourism Industry ◽  
Orienteering Problem ◽  
Complete Graphs ◽  
Roulette Wheel Selection ◽  
Roulette Wheel

Orienteering problem (OP) is an NP-Hard graph problem. The nodes of the graph are associated with scores or rewards and the edges with time delays. The goal is to obtain a Hamiltonian path connecting the two necessary check points, i.e. the source and the target along with a set of control points such that the total collected score is maximized within a specified time limit. OP finds application in several fields like logistics, transportation networks, tourism industry, etc. Most of the existing algorithms for OP can only be applied on complete graphs that satisfy the triangle inequality. Real-life scenario does not guarantee that there exists a direct link between all control point pairs or the triangle inequality is satisfied. To provide a more practical solution, we propose a stochastic greedy algorithm (RWS_OP) that uses the roulette wheel selectionmethod, does not require that the triangle inequality condition is satisfied and is capable of handling both complete as well as incomplete graphs. Based on several experiments on standard benchmark data we show that RWS_OP is faster, more efficient in terms of time budget utilization and achieves a better performance in terms of the total collected score ascompared to a recently reported algorithm for incomplete graphs.

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