Application of Lagrangian relaxation to computer network control

Lagrangian Relaxation Neural Network for Unit Commitment

This paper presents a novel method for unit commitment by synergistically combining Lagrangian relaxation for constraint handling with Hopfield-type recurrent neural networks for fast convergence to the minimum. The key idea is to set up a Hopfieldtype network using the negative dual as its energy function. This network is connected to “neuron-based dynamic programming modules” that make full u...

A Lagrangian relaxation network for graph matching

A Lagrangian relaxation network for graph matching is presented. The problem is formulated as follows: given graphs G and g, find a permutation matrix M that brings the two sets of vertices into correspondence. Permutation matrix constraints are formulated in the framework of deterministic annealing. Our approach is in the same spirit as a Lagrangian decomposition approach in that the row and c...

Lagrangian Relaxation Applied to Sparse Global Network Alignment

Data on molecular interactions is increasing at a tremendous pace, while the development of solid methods for analyzing this network data is lagging behind. This holds in particular for the field of comparative network analysis, where one wants to identify commonalities between biological networks. Since biological functionality primarily operates at the network level, there is a clear need for...

A Lagrangian relaxation approach for network inventory control of stochastic revenue management with perishable commodities

Airline seat inventory control is the allocation of seats in the same cabin to different fare classes such that the total revenue is maximized. Seat allocation can be modelled as dynamic stochastic programs, which are computationally intractable in network settings. Deterministic and probabilistic mathematical programming models are therefore used to approximate dynamic stochastic programs. The...

CP-based Lagrangian Relaxation for a Multimedia Application