We study the problem of minimizing a nonnegative separable concave function over a compact feasible set. We approximate this problem to within a factor of 1+epsilon by a piecewise-linear minimization problem over the same feasible set. Our main result is that when the feasible set is a polyhedron, the number of resulting pieces is polynomial … Read more
The increasing diffusion of Automatic Meter Reading (AMR) has raised many concerns about the protection of personal data related to energy, water or gas consumption, from which details about the habits of the users can be inferred. On the other hand, aggregated measurements about consumption are crucial for several goals, including resource provisioning, forecasting, and … Read more
We show that global optimization techniques, based on interval analysis and constraint propagation, succeed in solving the classical problem of optimization of the Belgium gas network. Citation Published as Inria Research report RR-7796, November 2011. Article Download View Global optimization of pipe networks by the interval analysis approach: the Belgium network case
We are given a digraph G = (N, A), where each arc is colored with one among k given colors. We look for a spanning arborescence T of G rooted at a given node and having minimum changeover cost. We call this the Minimum Changeover Cost Arborescence problem. To the authors’ knowledge, it is a … Read more
Designing a network able to route a set of non-simultaneous demand vectors is an important problem arising in telecommunications. The problem can be seen a two-stage robust program where the recourse function consists in choosing the routing for each demand vector. Allowing the routing to change arbitrarily as the demand varies yields a very difficult … Read more
We propose a distributed algorithm for solving the optimization problem Basis Pursuit (BP). BP finds the least L1-norm solution of the underdetermined linear system Ax = b and is used, for example, in compressed sensing for reconstruction. Our algorithm solves BP on a distributed platform such as a sensor network, and is designed to minimize … Read more
The aim of operational train timetabling is to find a conflict free timetable for a set of passenger and freight trains with predefined stopping time windows along given routes in an infrastructure network so that station capacities and train dependent running and headway times are observed. Typical models for this problem are based on time-discretized … Read more
We formulate minmax flow problems as a DC. optimization problem. We then apply a DC primal-dual algorithm to solve the resulting problem.The obtained computational results show that the proposed algorithm is efficient thanks to particular structures of the minmax flow problems. Citation 1. An L. T. H. and Tao P. D., The DC (Difference of … Read more
We propose a modification to the (generalized) bundle scheme for minimization of a convex nondifferentiable sum-function in the case where some of the components are “easy”, that is, they are Lagrangian functions of explicitly known convex programs with “few” variables and constraints. This happens in many practical cases, particularly within applications to combinatorial optimization. In … Read more
This paper presents a study on reliable single and multiple allocation hub-and-spoke network design problems where disruptions at hubs and the resulting hub unavailability can be mitigated by backup hubs and alternative routes. It builds nonlinear mixed integer programming models and presents linearized formulas. To solve those difficult problems, Lagrangian relaxation and Branch-and-Bound methods are … Read more