GNOM - Grup d'Optimització Numèrica i Modelització
El treball del grup comprèn l'optimització numèrica, la modelització de problemes resolubles amb optimització, i l'aplicació de tècniques adients a problemes de l'enginyeria, la indústria, la logística i les tecnologies de la informació. L'optimització numèrica inclou l'estudi de les propietats del problemes estudiats, l'anàlisi de nous algorismes d'optimització (lineal, no lineal, contínua, entera i combinatòria), el desenvolupament de procediments numèrics per a la seva implementació computacional eficient i la comparació amb algorismes previs, si existeixen. La part de modelització implica la cerca de formulacions escaients que permetin la resolució de problemes reals, sovint de gran dimensió. Els problemes reals en que el grup està treballant actualment són: protecció i privacitat de dades estadístiques; i generació òptima d'electricitat en un entorn multimercat.
The group works on both the numerical optimisation and the modelling of problems that can be solved through optimisation. Its work on numerical optimisation includes the analysis of new optimisation algorithms (linear, nonlinear, continuous and integer) and their convergence, the development of numerical procedures for their efficient computational implementation, and the comparison to existing algorithms. The work on modelling focuses on the solution of real problems, which are often large-scale, by finding an equivalentmathematical formulation leading to an optimisation problem, and applying a suitable solver, that has either been specially developed or is commercially available. The modelling languages that are available are used.
The group works on both the numerical optimisation and the modelling of problems that can be solved through optimisation. Its work on numerical optimisation includes the analysis of new optimisation algorithms (linear, nonlinear, continuous and integer) and their convergence, the development of numerical procedures for their efficient computational implementation, and the comparison to existing algorithms. The work on modelling focuses on the solution of real problems, which are often large-scale, by finding an equivalentmathematical formulation leading to an optimisation problem, and applying a suitable solver, that has either been specially developed or is commercially available. The modelling languages that are available are used.
Collections in this community
-
Articles de revista [107]
-
Llibres [1]
-
Reports de recerca [35]
-
Working papers [1]
Recent Submissions
-
Weightedness measures from inequality systems
(2025-07)
Article
Restricted access - publisher's policyA simple game is a cooperative game where some coalitions among players or voters became the (monotonic) set of winning coalitions, and the other ones form the set of losing coalitions. It is well-known that weighted voting ... -
Power system modeling tools for sustainable development: a review
(Institute of Electrical and Electronics Engineers (IEEE), 2024)
Conference lecture
Open AccessThe green growth paradigm aims to harmonize economic growth with environmental sustainability. Electricity is essential for economic development, and if its associated carbon emissions are sufficiently low, it is a key ... -
A new mathematical optimization-based method for the m-invariance problem
(Springer, 2025-02-08)
Article
Open AccessPrivacy preserving dynamic data publication aims at protecting data while simultaneously preserving its utility when the data is published dynamically. For static data (i.e., data published only once), privacy is based on ... -
Heuristic algorithm tool for planning mass vaccine campaigns
(Emerald Publishing Limited, 2025-04-21)
Article
Open AccessPurpose The planning of massive vaccination campaigns often falls to nongovernmental organizations that have to face the critical challenge of vaccinating the largest number of people in the shortest time. This study aims ... -
Heterogeneity of treatment response to beta-blockers in the treatment of portal hypertension: a systematic review
(2024-02)
Article
Open AccessBackground: It has been suggested that a relevant proportion of patients do not respond to nonselective beta-blockers (NSBB)s, which raises questions regarding the need for individualized therapy. The existence of potential ... -
The Chebyshev center as an alternative to the analytic center in the feasibility pump
(2023-06-07)
Article
Open AccessAs a heuristic for obtaining feasible points of mixed integer linear problems, the feasibility pump (FP) generates two sequences of points: one of feasible solutions for the relaxed linear problem; and another of integer ... -
An exact approach for the reliable fixed-charge location problem with capacity constraints
(2023-11-16)
Article
Open AccessIntroducing capacities in the reliable fixed charge location problem is a complex task since successive failures might yield in high facility overloads. Ideally, the goal consists in minimizing the total cost while keeping ... -
Citicoline for the management of patients with traumatic brain injury in the acute phase: a systematic review and meta-analysis
(Multidisciplinary Digital Publishing Institute (MDPI), 2023-02-01)
Article
Open AccessBackground: Citicoline or CDP-choline is a neuroprotective/neurorestorative drug used in several countries for the treatment of traumatic brain injury (TBI). Since the publication of the controversial COBRIT, the use of ... -
Thirty years of optimization-based SDC methods for tabular data
(2023-01)
Article
Open AccessIn 1966 Bacharach published in Management Science a work on matrix rounding problems in two-way tables of economic statistics, formulated as a network optimization problem. This is likely the first application of ... -
On solving large-scale multistage stochastic optimization problems with a new specialized interior-point approach
(2023-04)
Article
Open AccessA novel approach based on a specialized interior-point method (IPM) is presented for solving largescale stochastic multistage continuous optimization problems, which represent the uncertainty in strategic multistage and ... -
New interior-point approach for one- and two-class linear support vector machines using multiple variable splitting
(2022-09-29)
Article
Open AccessMultiple variable splitting is a general technique for decomposing problems by using copies of variables and additional linking constraints that equate their values. The resulting large optimization problem can be solved ... -
An optimization-based decomposition heuristic for the microaggregation problem
(Springer, 2022)
Conference report
Open AccessGiven a set of points, the microaggregation problem aims to find a clustering with a minimum sum of squared errors (SSE), where the cardinality of each cluster is greater than or equal to k. Points in the cluster are ...