Estimation of all-terminal network reliability using press forward GA with stochastic selection method
Main Article Content
Abstract
Network reliability is an important measure of how well the network meets its design aim and mathematically is the probability that a network will perform communication efficiently for at least a given period of time. The reliability analysis is used for determining the probability of correct functioning of a system in terrain conditions. Estimating the all-terminal network reliability is an NP-hard problem, the press forward Genetic Algorithm is also an alternative to solve the problem of all-terminal network reliability. This paper presents a reliability evaluation method by using a feed-forward genetic algorithm with a random selection of nodes and links i.e., estimate the network reliability such that the flow is not less than a given threshold. To verify the efficiency of an algorithm, various sets of runs are applied to identify the most reliable network and the algorithm is tested on the network size of 2,4,6,8, --------256 nodes with link N(N-1)/2. The results of the algorithm are obtained for all-terminal reliability problem based on close analysis of the complexity of the network. Our assumption for reliability evaluation of node 1 to node N, with link reliability of 50%. Another result of the proposed GA approach is the significant reduction in computational time.
Downloads
Metrics
Article Details
You are free to:
- Share — copy and redistribute the material in any medium or format for any purpose, even commercially.
- Adapt — remix, transform, and build upon the material for any purpose, even commercially.
- The licensor cannot revoke these freedoms as long as you follow the license terms.
Under the following terms:
- Attribution — You must give appropriate credit , provide a link to the license, and indicate if changes were made . You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
- No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
Notices:
You do not have to comply with the license for elements of the material in the public domain or where your use is permitted by an applicable exception or limitation .
No warranties are given. The license may not give you all of the permissions necessary for your intended use. For example, other rights such as publicity, privacy, or moral rights may limit how you use the material.