Sheikh, A.A., Felemban, E., Alhindi, A., Naseer, A., Ghaleb, M. and Lbath, A. (2017) OpToGen-A Genetic Algorithm Based Framework for Optimal Topology Generation for Linear Networks. 2017 13th IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), Cluj-Napoca, Romania, 7-9 September 2017, 255-262.
https://doi.org/10.1109/ICCP.2017.8117012

has been cited by the following article:

• TITLE: Design of a Heuristic Topology Generation Algorithm in Multi-Domain Optical Networks

  AUTHORS: Lei Wang, Huayang Feng, Li Lin, Li Du

  KEYWORDS: Topology Generation, Genetic Algorithm, Crossover Operation, Topology Aggregation

  JOURNAL NAME: Communications and Network, Vol.10 No.3, July 19, 2018

  ABSTRACT: Designing an excellent original topology not only improves the accuracy of routing, but also improves the restoring rate of failure. In this paper, we propose a new heuristic topology generation algorithm—GA-PODCC (Genetic Algorithm based on the Pareoto Optimality of Delay, Configuration and Consumption), which utilizes a genetic algorithm to optimize the link delay and resource configuration/consumption. The novelty lies in designing the two stages of genetic operation: The first stage is to pick the best population by means of the crossover, mutation, and selection operation; The second stage is to select an excellent individual from the best population. The simulation results show that, using the same number of nodes, GA-PODCC algorithm improves the balance of all the three optimization objectives, maintaining a low level of distortion in topology aggregation.