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Efficient Mixed Integer Linear Programming Approaches to Dynamic Path Restoration 12

Efficient Mixed Integer Linear Programming Approaches to Dyn...

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12th IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom)

作者： Rubtsov, Alexander Bauwens, Bruno Shmelkin, Dmitri Rudenko, Elizaveta Lavrov, Alexey HSE Univ Fac Comp Sci Moscow Russia Independent Univ Moscow Moscow Russia HSE Univ Fac Math Moscow Russia

ISBN: (纸本)9798350351866;9798350351859

We consider the problem of single link failure in an elastic optical network, (also known as flex-grid WDM network). The task is to reroute optical connections that go through the broken link using free capacity of other links of the network. Nowadays, dynamic restoration gains popularity, in which the possiblity of rerouting is only inspected after a link failure is detected. Since the problem of recovery is NP-hard, heuristic algorithms are used to either find such routes, or suggest that the routes do not exist. In order to understand the quality of these heuristics, often mixed integer linear programming is used to obtain exact positive and negative answers. We present a detailed such model that checks whether restoration is possible without the use of additional regenerators. This means, that the new light paths need to satisfy a length constraint. As preprossing we apply a trimming procedure that takes advantage of this length constraint, and significantly speeds up the evaluation of these models. Our model is more general, and besides solving the problem of link restoration, also solves the full problem of wavelength and spectrum assignment.

关键词： Mixed Integer Linear Programming routing and spectrum allocation problem Combinatorial Optimization

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Dynamic Subpopulation Number Control for Solving routing and spectrum allocation problems in Elastic Optical Networks 3

Dynamic Subpopulation Number Control for Solving Routing and...

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3rd European Network Intelligence Conference (ENIC)

作者： Przewozniczek, Michal Wroclaw Univ Sci & Technol Dept Computat Intelligence Wroclaw Poland

ISBN: (纸本)9781509034550

Coevolution is a well-known way of population diversity preservation in the field of Evolutionary Computation. Usually, the methods that use coevolution are effective in solving hard optimization problems, because they are less likely to stuck in local optima. Therefore, they are more capable of reaching a breakthrough, find new, promising regions in the solution search space and propose solutions of better quality. One of the main drawbacks of coevolution is the high computation cost of many coevolving subpopulations maintenance. If the coevolution is used, the determination of subpopulations number is crucial and may be very challenging. Therefore, the strategies of dynamic subpopulation number control (SDSNC). When SDSNC is used, the number of coevolving subpopulations is automatically adjusted to the current solution search state and changes during the method run. Therefore, this paper analyzes, the application of the recent SDSNC propositions to the multi-population method designed for solving the routing and spectrum allocation with Joint Anycast and Unicast (RSA-JAU).

关键词： Coevolution Dynamic Subpopulation Management Dynamic Subpopulation Number Control Evolutionary Algorithms Linkage Learning Elastic Optical Networks routing and spectrum allocation problem Anycasting

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Towards finding an effective uniform and single point crossover balance for optimization of Elastic Optical Networks 2

Towards finding an effective uniform and single point crosso...

引用

2nd European Network Intelligence Conference (ENIC)

作者： Przewozniczek, Michal Wroclaw Univ Technol Dept Computat Intelligence PL-50370 Wroclaw Poland

ISBN: (纸本)9781467375924

The new promising technologies in the network communication field bring the possibilities of faster and more safe information sending. However, the new technologies bring up new computation problems as well. The network flow may be organized in a better way with respect to different criteria. It is common that such problems are hard not only because of their size, but also due to their NP-complete or NP-hard nature. The Genetic Algorithms are commonly known and widely used tools, which allow to effectively solve such problems. It is usual that a Genetic Algorithm is adjusted to the solved problem. The adjustments may also take into consideration the type of crossover operator used, which is one of the most primary genetic operators. Therefore, this paper takes into consideration the NP-hard routing and spectrum allocation with Joint Anycast and Unicast problem and presents the results of extensive research performed to check the influence of crossover type on the overall method effectiveness.

关键词： Evolutionary Algorithms single point crossover uniform crossover Elastic Optical Networks routing and spectrum allocation problem anycasting

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