Decomposition methods for large-scale network expansion problems

Decomposition Methods and Network Design Problems

Domain Decomposition Solvers for Large Scale Industrial Finite Element Problems

Today, systems of equations with more than one million unknowns need to be solved. To solve such systems in a reasonable time requires the use of powerful parallel computers. The European project PARASOL aimed to design and develop a library of scalable sparse matrix solvers for distributed memory computers. Parallab was a partner in the project and developed the domain decomposition solver DD....

Decomposition-based evolutionary algorithm for large scale constrained problems

Cooperative Coevolutionary algorithms (CC) have been successful in solving large scale optimization problems. The performance of CC can be improved by decreasing the number of interdependent variables among decomposed subproblems. This is achieved by first identifying dependent variables, and by then grouping them in common subproblems. This approach has potential because so far no grouping tec...

Decomposition Methods for Large-Scale Optimization of Power Systems

Variable renewable power sources are being integrated into power systems across the world. This restructuring process requires extensions of most parts of the power system infrastructure: generation, transmission, as well as storage capacity. Joint optimization of infrastructure extension and operation is a powerful method to identify technical solutions with minimal economic costs. This optimi...

Decomposition methods based on projected gradient for network equilibrium problems

In this work we consider the symmetric network equilibrium problem formulated as convex minimization problem whose variables are the path flows. In order to take into account the difficulties related to the large dimension of real network problems we adopt a column generation strategy and we employ a gradient projection method within an inexact decomposition framework. We present a general deco...