Michal Przewozniczek

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The major objective of this paper is to deploy an effective evolutionary algorithm (EA) for the congestion problem in connection-oriented networks. The network flow is modeled as non-bifurcated multicommodity flow. The main novelty of this work is that the proposed evolutionary algorithm consists of two levels. The high level applies typical EA operators.(More)
Keywords: Genetic algorithm Large solution space size MuPPetS Gene patterns Linkage learning Optimization Elastic optical networks Routing and spectrum allocation Anycasting a b s t r a c t The fast social and economic development observed in the recent years brings up new challenging optimization problems. These problems are often very hard not only(More)
In this paper we address the problem of working paths optimization in survivable MPLS network. We focus on an existing facility network, in which only network flows can be optimized to provide network survivability using the local repair strategy. The main goal of our work is to develop an effective evolutionary algorithm (EA) for considered optimization(More)