REALOPT - 2016 - Annual activity report

REALOPT

REALOPT - 2016

Project-Team Realopt

Members

Overall Objectives

Research Program

Introduction
Polyhedral approaches for MIP
Decomposition and reformulation approaches
Integration of Artificial Intelligence Techniques in Integer Programming
Robust Optimization
Polyhedral Combinatorics and Graph Theory

Application Domains

Introduction
Network Design and Routing Problems
Packing and Covering Problems
Planning, Scheduling, and Logistic Problems

Highlights of the Year

New Software and Platforms

BaPCod : A generic Branch-And-Price Code

New Results

Improving Branch-and-Price Methods
Aggregation Techniques
Review of Algorithmic Enhancements for Benders Decomposition
Vehicle Routing Problems
Production Scheduling Problems
Scheduling and Placement for HPC
Network Design Problems
Strategic Planning of Phytosanitary treatments in Wineries
Two-dimensional Guillotine-cut Bounded Knapsack Problem
Matching-Based Allocation Strategies in Cloud Platforms
On Sets Avoiding Distance 1

Bilateral Contracts and Grants with Industry

Contract with EDF on robust maintenance planning
Collaboration with ERTUS on phytosanitary treatment planning
Collaboration with St-Gobain Recherche on glass cutting
Collaboration with Greycon Ltd. on industrial cutting
Collaboration with SNCF on timetable and rolling stock rotation planning

Partnerships and Cooperations

Regional Initiatives
National Initiatives
International Initiatives
International Research Visitors

Dissemination

Promoting Scientific Activities
Teaching - Supervision - Juries
Popularization

Bibliography

Major publications
Publications of the year
References in notes

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2016 Project-Team Activity Report

REALOPT

Reformulations based algorithms for Combinatorial Optimization

Research centre: Bordeaux - Sud-Ouest

In partnership with: CNRS, Université de Bordeaux

In collaboration with: Institut de Mathématiques de Bordeaux (IMB), Laboratoire Bordelais de Recherche en Informatique (LaBRI)

Field: Applied Mathematics, Computation and Simulation

Theme: Optimization, machine learning and statistical methods

Keywords:

Computer Science and Digital Science:

7.2. - Discrete mathematics, combinatorics
7.3. - Optimization
7.9. - Graph theory

Other Research Topics and Application Domains:

6.5. - Information systems