Applying MOEAs to solve the static Routing and Wavelength Assignment problem in optical WDM networks

被引:14
作者
Rubio-Largo, Alvaro [1 ]
Vega-Rodriguez, Miguel A. [1 ]
机构
[1] Univ Extremadura, Dept Comp & Commun Technol, Escuela Politecn, Caceres 10003, Spain
关键词
Routing and Wavelength Assignment; Wavelength Division Multiplexing; Multiobjective Optimization; Differential Evolution; Variable Neighborhood Search; Optical networks; MULTIOBJECTIVE OPTIMIZATION; DIFFERENTIAL EVOLUTION; ALGORITHMS; PRINCIPLES; CONVERSION; SEARCH; DESIGN;
D O I
10.1016/j.engappai.2013.03.005
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Wavelength-Division Multiplexing (WDM) in optical networks has revolutionized the Telecommunication field. This technology is able to exploit the enormous bandwidth capability of this kind of networks, allowing communication between end users via all-optical WDM channels (lightpath). Given a set of demands, the problem of setting up lightpaths by routing and assigning a wavelength to each connection is known as Routing and Wavelength Assignment (RWA) problem. There are two types of connection demands: static (demands are given in advance) and dynamic (demands are given in real-time). In this paper we present two different Multiobjective Evolutionary Algorithms (MOEA) with the aim of solving the static RWA problem. The first one is a population-based algorithm, the Differential Evolution (DE), but incorporating the Pareto Tournament concept (DEPT). The second one is a multiobjective version of the Variable Neighborhood Search (VNS), MO-VNS. In order to prove the goodness of our metaheuristics, we have compared them with the standard Fast Non-Dominated Sorting Genetic Algorithm (NSGA-II), typical heuristics in the Telecommunication field, and different varieties of Multiobjective Ant Colony Optimization Algorithms. On the whole, we conclude that our approaches have obtained very promising results. (C) 2013 Elsevier Ltd. All rights reserved.
引用
收藏
页码:1602 / 1619
页数:18
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