Routing and Wavelength Assignment in Optical Networks Using Genetic Algorithms

Beckmann, Dirk; Killat, Ulrich

doi:10.1002/ett.4460100509

Cited by 10 publications

(4 citation statements)

References 7 publications

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“…Although GA is an algorithm that usually presents robust results, as it is a meta-heuristic method, the solution can converge to a local minimum, presenting a false optimal response. However, this premature convergence can be minimized with an appropriate adjustment in the number of generations, population size and genetic operators [37,38].…”

Section: Genetic Algorithmmentioning

confidence: 99%

Evolutionary Strategy for Practical Design of Passive Optical Networks

et al. 2022

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Passive optical networks (PONs) are an important and interesting technology for broadband access as a result of the growing demand for bandwidth over the past 10 years. An arduous and complex step in the design of such networks involves determining the placement of equipment, optical fiber cables and several other parameters relevant to the proper functioning of the network. In this paper, we propose an evolutionary strategy to optimize the infrastructure design of PONs by using genetic algorithm technique. This meta-heuristic is capable of elaborating fast, automatic and efficient solutions for the design and planning of PONs. Our proposal has been developed using real maps, aiming to minimize deployment costs and time spent to carry out PON projects, achieving pre-defined quality criteria. We considered, in our simulations, two scenarios (non-dense and dense), four possible topologies and two regions of interest. The non-dense consists of a scenario in which subscribers are distributed in a dispersed manner in the region of interest. The dense has a considerably higher number of subscribers distributed in a very close way to each other. Based on the obtained results, the potential of our proposal is quite clear, as well as its relevance from a technical, economic, and commercial point of view.

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Section: Genetic Algorithmmentioning

confidence: 99%

Evolutionary Strategy for Practical Design of Passive Optical Networks

et al. 2022

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“…Various heuristic methods have been proposed, such as genetic algorithms [9], graph-theoretic modeling [11], partition coloring [22], integer linear program [5,27]. A recent survey of various algorithms for the RWA problem can be found in [13].…”

Section: −δmentioning

confidence: 99%

Average-Case Performance Evaluation of Online Algorithms for Routing and Wavelength Assignment in WDM Optical Networks

2007

2007 IEEE International Parallel and Distributed Processing Symposium

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“…Various heuristic methods have been proposed, such as genetic algorithms [4], graph-theoretic modelling [5], partition colouring [14], integer linear program [2,16]. A recent survey of various algorithms for the RWA problem can be found in Ref.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of heuristic algorithms for routing and wavelength assignment in WDM optical networks

2010

International Journal of Parallel, Emergent and Distributed Sys

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We evaluate the average-case performance of eight offline heuristic algorithms to solve the routing and wavelength assignment (RWA) problem and the related throughput maximisation (TM) problem in wavelength division multiplexing optical networks. These algorithms are first-fit-decreasing (FFD), first-fit-increasing (FFI), best-fitdecreasing (BFD), best-fit-increasing (BFI), densest-fit-decreasing (DFD), densest-fitincreasing (DFI), random-fit-decreasing (RFD) and random-fit-increasing (RFI). Our experimental performance evaluation is conducted by extensive simulations on a wide range of WDM optical networks, including a mesh network, four real networks and three types of random networks. We find offline RWA algorithms and TM algorithms which perform better than previously studied online algorithms, namely, first-fit (FF), best-fit (BF), densest-fit (DF) and random-fit (RF). In particular, algorithm FFD (BFD, DFD and RFD, respectively) has better performance than algorithm FF (BF, DF and RF, respectively) for RWA, and algorithm FFI (BFI, DFI and RFI, respectively) has better performance than algorithm FF (BF, DF and RF, respectively) for TM.

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Routing and Wavelength Assignment in Optical Networks Using Genetic Algorithms

Cited by 10 publications

References 7 publications

Evolutionary Strategy for Practical Design of Passive Optical Networks

Evolutionary Strategy for Practical Design of Passive Optical Networks

Average-Case Performance Evaluation of Online Algorithms for Routing and Wavelength Assignment in WDM Optical Networks

Performance evaluation of heuristic algorithms for routing and wavelength assignment in WDM optical networks

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