University of the Basque Country University of the Basque Country

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Faculty of Science and Technology

Faculty of Science and Technology
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STOCHASTIC OPTIMIZATION GROUP (GOE)

 

Department (s)
Department (s):  Mathematics (UPV/EHU), Applied Mathematics (UPV/EHU),  Quantitative Methods for Economy and Business (UPV/EHU), Data Science – Machine Learning (BCAM), Data Science – Combinatorial Optimization (BCAM), Applied Mathematics, Materials Science and Engineering and Electronic Engineering (URJC)
 
Knowledge area
Operations Research, Mathematical Optimization, Applied Mathematics
PI: María Merino Maestre Co-IP: M. Araceli Garín Martín

Members

Unai Aldasoro Marcellán, Larraitz Aranburu Laka, Mª Isabel Eguia Ribero, Laureano F. Escudero Bueno, Imanol Gago Carro, Gorka Kobeaga Urriolabeitia, Celeste Pizarro Romero, Aitziber Unzueta Inchaurbe

Keywords

Combinatorial optimization, stochastic optimization, risk-management, exact and heuristic algorithms

Description

The Stochastic Optimization Group is a research group in mathematical optimization, deterministic and under uncertainty. We are focused in the theoretical and applied development of the optimization techniques, the design and implementation of algorithms for solving large-scale combinatorial optimization problems as well as stochastic multistage mixed 0-1 and quadratic problems. Moreover, we are interested in the development of efficient methodologies for obtaining optimal or quasioptimal bounds. This group research also in modeling risk averse environments. We use parallel computing with MPI and C++ with optimization software like COIN-OR and CPLEX. With respect to applications, we are interested in solving real problems on routing, assignment, location, distribution and logistics, in the following sectors: sanitary, energy and humanitarian emergency, among others.

Lines of Research

  1. Lineal, integer and mixed 0-1 optimization
  2. Quadratic and quadratic constrained optimization
  3. Stochastic optimization
  4. Combinatorial optimization
  5. Risk management
  6. Decomposition techniques for large scale problems
  7. Algorithms development: Fix and Relax, Branch and Fix Coordination, Lagrangian decomposition
  8. Parallel programming techniques
  9. Software: C++, COIN-OR, CPLEX, MPI
  10. Applications: sanitary, industrial, financial, logistic and socio-humanitarian sectors.

Equipment

    • Computational Services from SGI/IZO-SGIker computatonal cluster ARINA (UPV/EHU, GV/EJ, ERDF eta ESF)
    •  Quantitative Economy laboratory   (UPV/EHU)
Workstation Dell Precision T7500 under Linux, 64 bits, 2.4 Ghz, 12GbRAM, 8 cores.

Websitelink
https://www.ehu.eus/eu/web/goe 

Contact
maria.merino@ehu.eus