Heuristic algorithms for path selection in private ATM networks

2002 ◽  
Author(s):  
Xuedong Jiang ◽  
Tao Yang
Keyword(s):  
Heuristic Algorithms ◽  
Path Selection ◽  
Atm Networks

Identifying Multiple and Reasonable Paths in Transportation Networks: A Heuristic Approach

1997 ◽  
Vol 1607 (1) ◽  
pp. 31-37 ◽  
Author(s):  
Dongjoo Park ◽  
Laurence R. Rilett
Keyword(s):  
Travel Time ◽  
Shortest Path ◽  
Heuristic Algorithms ◽  
Transportation Networks ◽  
Multiple Criteria Decision Making ◽  
Path Selection ◽  
Multiple Criteria ◽  
Transportation Engineering ◽  
Shortest Path Algorithm ◽  
Shortest Path Algorithms

A fundamental component of many transportation engineering applications is the identification of the route between a given origin and destination. Typically, some type of shortest-path algorithm is used for this task. However, shortest-path algorithms are only applicable when a single criterion, such as minimizing travel time, is used for path selection. When multiple criteria, such as the mean and variance of travel time, are used for path selection, then alternative-path identification methods must be found. The present objective is to develop an algorithm that can identify multiple and reasonable routes in transportation networks so that multiple-criteria decision-making techniques can be used in route selection. First, the definitions of single and multiple routes from a transportation engineering perspective are examined. It is indicated that although the traditional k-shortest-path algorithms can find routes with similar route travel times, the routes may be too similar with respect to the links used and consequently are not appropriate for certain transportation applications. A definition of a reasonable path is developed on the basis of transportation engineering rather than purely mathematical considerations. Two k-reasonable-path algorithms are then illustrated. These algorithms can be used to identify multiple and reasonable routes in transportation networks. Lastly, the two heuristic algorithms were tested on a network from Bryan to College Station, Texas, and the results were compared with the results obtained with a traditional k-shortest-path algorithm. It was found that the reasonable-path algorithms can identify routes that are similar in route travel time but significantly different in terms of the links used.

scholarly journals A Comprehensive Analysis of ACO for Wireless Sensor Network Routing

2020 ◽  
Vol 9 (6) ◽  
pp. 547-551
Keyword(s):  
Wireless Sensor Networks ◽  
Sensor Networks ◽  
Greedy Algorithm ◽  
Network Lifetime ◽  
Heuristic Algorithms ◽  
Routing Algorithm ◽  
Optimal Path ◽  
Path Selection ◽  
Wireless Sensor ◽  
Route Management

The proliferations of IoT technologies and applications have led to an increased interest in Wireless Sensor Networks (and in particular, multi-hop networks). Wireless sensor networks are composed of small mobile terminals which have limited system resources. Due to this, these networks are vulnerable to changes in network status arising from changes in the network parameters such as, position / layout of sensors, signal strength, environmental conditions, etc. In addition, the network nodes are also constrained in terms of energy provided by the battery. It is an significant consideration to be accounted so as to prolong their operational time, since this adds to the network lifetime. Lot of research has gone into routing and transmission technologies for wireless sensor networks. Conventional routing mechanisms for WSNs still suffer from energy-hole problem caused by difficulties in adaptive route management. Thus, it is imperative that efficient routing mechanisms be developed in order to conserve energy and improve network lifetime. One popular approach is to use meta-heuristic algorithms for optimal path selection in a WSN route management system. A very popular meta-heuristic algorithm used for this objective is the Ant Colony Optimization (ACO) algorithms. ACO has been used as a base for many routing management systems. In this paper an extensive analysis of the performance of ACO based route selection mechanism is reported and also reporting a comparative analysis of efficacy of the ACO routing algorithm over the standard Greedy algorithm in finding routes with different count of sensor nodes and different count of ants. Then find that the ACO routing algorithm outdoes the Greedy algorithm with respect to the number of routes identified.

scholarly journals The Most Trustworthy Path Selection in Online Social Networks

2013 ◽  
Vol 2013 ◽  
pp. 1-10
Author(s):  
Lianggui Liu
Keyword(s):  
Social Networks ◽  
Online Social Networks ◽  
Heuristic Algorithms ◽  
Social Trust ◽  
Optimization Problems ◽  
Path Selection ◽  
Service Consumer ◽  
First Time ◽  
Selection Of

In online social networks, it is crucial for a service consumer to find the most trustworthy path to a target service provider from numerous social trust paths between them. The selection of the most trustworthy path (namely, optimal social trust path (OSTP)) with multiple end-to-end quality of trust (QoT) constraints has been proved to be NP-Complete. Heuristic algorithms with polynomial and pseudo-polynomial-time complexities are often used to deal with this challenging problem. However, existing solutions cannot guarantee the efficiency of searching; that is, they can hardly avoid obtaining partial optimal solutions during searching process. Quantum annealing uses delocalization and tunneling to avoid falling into local minima without sacrificing execution time. It has been proved to be a promising way to many optimization problems in recently published literature. In this paper, for the first time, QA based OSTP algorithm (QA_OSTP) is applied to the selection of the most trustworthy path. The experiment results show that QA based algorithm has better performance than its heuristic opponents.

Comparison of Meta-heuristic Algorithms on Benchmark Functions

2019 ◽  
Vol 2 (3) ◽  
pp. 508-517
Author(s):  
FerdaNur Arıcı ◽  
Ersin Kaya
Keyword(s):  
Heuristic Algorithms ◽  
Optimization Problems ◽  
Search Algorithm ◽  
Optimization Algorithms ◽  
Gravitational Search Algorithm ◽  
Differential Evolution Algorithm ◽  
Population Based ◽  
Time Interval ◽  
Bee Colony ◽  
Different Characteristics

Optimization is a process to search the most suitable solution for a problem within an acceptable time interval. The algorithms that solve the optimization problems are called as optimization algorithms. In the literature, there are many optimization algorithms with different characteristics. The optimization algorithms can exhibit different behaviors depending on the size, characteristics and complexity of the optimization problem. In this study, six well-known population based optimization algorithms (artificial algae algorithm - AAA, artificial bee colony algorithm - ABC, differential evolution algorithm - DE, genetic algorithm - GA, gravitational search algorithm - GSA and particle swarm optimization - PSO) were used. These six algorithms were performed on the CEC’17 test functions. According to the experimental results, the algorithms were compared and performances of the algorithms were evaluated.

Segmentation of Brain Tumors using Meta Heuristic Algorithms

2014 ◽  
Vol 2014 (1) ◽  
pp. 1-10 ◽  
Author(s):  
Jobin Christ ◽  
◽  
S. Sivagowri ◽  
Ganesh Babu ◽  
◽  
...  
Keyword(s):  
Brain Tumors ◽  
Heuristic Algorithms

Resource-Aware Path Selection in Heterogeneous Self-Organizing Wireless Networks

2010 ◽  
Vol E93-B (12) ◽  
pp. 3647-3650
Author(s):  
Bongjhin SHIN ◽  
Hoyoung CHOI ◽  
Daehyoung HONG
Keyword(s):  
Wireless Networks ◽  
Path Selection ◽  
Resource Aware ◽  
Self Organizing

Two Enhanced Heuristic Algorithms for the Minimum Initial Marking Problem of Petri Nets

2009 ◽  
Vol E92-A (11) ◽  
pp. 2732-2744
Author(s):  
Satoru OCHIIWA ◽  
Satoshi TAOKA ◽  
Masahiro YAMAUCHI ◽  
Toshimasa WATANABE
Keyword(s):  
Petri Nets ◽  
Heuristic Algorithms

Two Heuristic Algorithms for the Minimum Initial Marking Problem of Timed Petri Nets

2013 ◽  
Vol E96.A (2) ◽  
pp. 540-553
Author(s):  
Satoru OCHIIWA ◽  
Satoshi TAOKA ◽  
Masahiro YAMAUCHI ◽  
Toshimasa WATANABE
Keyword(s):  
Petri Nets ◽  
Heuristic Algorithms ◽  
Timed Petri Nets
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