Displaying similar documents to “Network flow optimization for restoration of images.”

Quasi-hierarchical evolution algorithm for flow assignment in survivable connection-oriented networks

Michal Przewozniczek, Krzysztof Walkowiak (2006)

International Journal of Applied Mathematics and Computer Science

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The main objective of this paper is to develop an effective evolutionary algorithm (EA) for the path-assignment problem in survivable connection-oriented networks. We assume a single-link failure scenario, which is the most common and frequently reported failure event. Since the network flow is modeled as a non-bifurcated multicommodity flow, the discussed optimization problem is NP-complete. Thus, we develop an effective heuristic algorithm based on an evolutionary algorithm. The main...

Inequality-sum : a global constraint capturing the objective function

Jean-Charles Régin, Michel Rueher (2005)

RAIRO - Operations Research - Recherche Opérationnelle

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This paper introduces a new method to prune the domains of the variables in constrained optimization problems where the objective function is defined by a sum y = Σ x i , and where the integer variables x i are subject to difference constraints of the form x j - x i ≤ c . An important application area where such problems occur is deterministic scheduling with the mean flow time as optimality criteria. This new constraint is also more general than a sum constraint defined on a set of ordered variables. Classical...

Ant algorithm for flow assignment in connection-oriented networks

Krzysztof Walkowiak (2005)

International Journal of Applied Mathematics and Computer Science

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This work introduces ANB (bf Ant Algorithm for bf Non-bf Bifurcated Flows), a novel approach to capacitated static optimization of flows in connection-oriented computer networks. The problem considered arises naturally from several optimization problems that have recently received significant attention. The proposed ANB is an ant algorithm motivated by recent works on the application of the ant algorithm to solving various problems related to computer networks. However, few works concern...

Anycasting in connection-oriented computer networks: Models, algorithms and results

Krzysztof Walkowiak (2010)

International Journal of Applied Mathematics and Computer Science

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Our discussion in this article centers around various issues related to the use of anycasting in connection-oriented computer networks. Anycast is defined as a one-to-one-of-many transmission to deliver a packet to one of many hosts. Anycasting can be applied if the same content is replicated over many locations in the network. Examples of network techniques that apply anycasting are Content Delivery Networks (CDNs), Domain Name Service (DNS), Peer-to-Peer (P2P) systems. The role of...

Separable convexification and DCA techniques for capacity and flow assignment problems

P. Mahey, Thai Q. Phong, H. P. L. Luna (2001)

RAIRO - Operations Research - Recherche Opérationnelle

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We study a continuous version of the capacity and flow assignment problem (CFA) where the design cost is combined with an average delay measure to yield a non convex objective function coupled with multicommodity flow constraints. A separable convexification of each arc cost function is proposed to obtain approximate feasible solutions within easily computable gaps from optimality. On the other hand, DC (difference of convex functions) programming can be used to compute accurate upper...

The inverse maximum flow problem considering norm

Adrian Deaconu (2008)

RAIRO - Operations Research

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The problem is to modify the capacities of the arcs from a network so that a given feasible flow becomes a maximum flow and the maximum change of the capacities on arcs is minimum. A very fast ⋅log()) time complexity algorithm for solving this problem is presented, where is the number of arcs and is the number of nodes of the network. The case when both, lower and upper bounds of the flow can be modified so that the given feasible flow becomes a maximum flow is also discussed. The...