Solving multi-objective routing and wavelength assignment in WDM network using hybrid evolutionary computation approach

Journal article

Authors/Editors

NARUEMON WATTANAPONGSAKORN

Strategic Research Themes

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Publication Details

Author list: Leesutthipornchai P., Charnsripinyo C., Wattanapongsakorn N.

Publisher: Elsevier

Publication year: 2010

Journal: Computer Communications (0140-3664)

Volume number: 33

Issue number: 18

Start page: 2246

End page: 2259

Number of pages: 14

ISSN: 0140-3664

eISSN: 1873-703X

URL: https://www.scopus.com/inward/record.uri?eid=2-s2.0-78049385186&doi=10.1016%2fj.comcom.2010.07.029&partnerID=40&md5=39ef69fafb5e1c57b34d5877eeec6c03

Languages: English-Great Britain (EN-GB)

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Abstract

Routing and wavelength assignment (RWA) is a well-known issue in wavelength division multiplexing (WDM) optical networks. In this paper, we present RWA design for WDM networks by considering multiple design objectives which are maximizing the number of traffic demands to be served and minimizing the number of wavelength channels to be assigned. A hybrid evolutionary computation approach consisting of genetic algorithm for routing allocation with minimum degree first for wavelength assignment (GA-MDF) and the fast non-dominated sorting genetic algorithm (NSGA-II) to search for non-dominated solutions is applied for solving the multi-objective RWA network design problem. The hybrid evolutionary algorithm is used as a meta-heuristic technique for obtaining good solutions for various problem sizes. The obtained results are provided as candidate choices or non-dominated front. We compare the simulation results obtained from the NSGA-II with those obtained from the traditional Weighted-Sum approach. Numerical results show that our hybrid evolutionary computation approach is effective in solving the multi-objective RWA problem. The GA-MDF can outperform the FAR-FF method in both design objectives. In addition, the solutions from the NSGA-II are more diverse on the multi-objective space than those of the Weighted-Sum method. We also apply a Pruned mechanism to help cutting off numerous non-dominated solutions for making decision on the final solution. ฉ 2010 Elsevier B.V. All rights reserved.

Keywords

Multi-objective genetic algorithm, Routing and wavelength assignment, WDM network