
ANR project SAGA
Structural Approximation for Geometric Algorithms.
(in collaboration with Lilian Buzer,
Xavier Goaoc,
Claire Mathieu,
Frédéric Meunier)
Combinatorial optimization arises naturally in a variety of resource management problems in public transportation companies, industrial manufacturing, financial and health-care institutions. Standing out are two categories of optimization problems, packing and covering, with applications in material and manpower planning, scheduling, routing, investment and resource allocation. The sad fact is that these problems are not only NP-hard, but also provably hard to approximate: for instance, no algorithm can approximate set-cover within a logarithmic multiplicative factor or independent set within a polynomial multiplicative factor. Even worse, with the proliferation of ubiquitous data-collecting devices and fast distributed data-sharing capabilities, the inputs to these problems are so large and complex that traditional computational ideas are infeasible. The task of finding efficient, reliable (provably good) and flexible solutions to packing and covering problems remains a challenge with high potential impact.