Float and Combinatorics

Securing and sizing networks (urban, IT, telecoms, etc.), optimizing the routing of flows (financial, information, personnel, products), logistics and transport problems (road, air and rail) represent real challenges for industry. The underlying optimization problems most often boil down to combinatorial models, which are essential building blocks for understanding complex systems.

This course is designed to complement training in algorithmic approaches specific to combinatorial optimization problems in graphs. The course aims to explain how to use the tools of mathematical programming (typically integer and linear programming) to guide combinatorial algorithms towards optimal solutions or, when this proves too complex, good approximate solutions. The aim is to master the basic models and techniques used in strategies for solving a wide variety of complex problems.

Introduction to OR

# Flow optimization in networks: basic models and algorithms

# Polyhedra and combinatorics: primal-dual algorithms and linear programming-based approximation algorithms