Table of Contents
Journal of Artificial Evolution and Applications
Volume 2008, Article ID 536913, 20 pages
Research Article

Genetic Algorithm for Finding Minimal Cost Light Forest of Multicast Routing on WDM Networks

Department of Computer Science and Information Engineering, National Changhua University of Education, Changhua City 500, Taiwan

Received 12 April 2007; Revised 6 September 2007; Accepted 13 January 2008

Academic Editor: Shengxiang Yang

Copyright © 2008 Der-Rong Din. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Wavelength division multiplexing (WDM) is an important technique to make use of the large amount of bandwidth in optical fibers to meet the bandwidth requirements of applications. Multicast is the transmission of information from one source to multiple destinations simultaneously. Given a multicast request in a WDM network, the goal is to find a set of light trees, the assigned wavelengths of light trees, and construct a light forest. In this paper, the minimal cost multicast routing problem (MCMRP) on WDM networks with tap-and-continue (TaC) nodes is defined and studied. A new cost model which consists of the wavelength usage and communication cost is defined. The objective is to minimize the sum of the cost of used wavelengths and the communication cost of the light forest. Specifically, the formulation for the WDM multicast routing problem is given. Because the MCMRP is NP-hard, two genetic algorithms (GAs) are proposed to solve this problem. In the proposed GAs, a path-oriented encoding chromosome is used to represent the routing paths. These routing paths are used to construct source-based light forests to represent a feasible solution to the multicast request. Moreover, to speed up the convergence of GAs, a farthest-first greedy heuristic algorithm is proposed and used to generate one of the initial chromosomes. Simulation results demonstrate that the proposed GAs can run efficiently.