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Efficiency of the Simplex Method: Quo vadis Hirsch conjecture?
January 18 - 21, 2011
Organizing Committee |
Scientific Overview |
Speaker List
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Organizing Committee
Margaret Bayer
(University of Kansas, Mathematics)
Jesus De Loera
(University of California, Davis (UC Davis), Mathematics)
Antoine Deza
(McMaster University)
Gil Kalai
(Hebrew University, Institute of Mathematics)
Shanghua Teng
(University of Southern California (USC))
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Scientific Overview
Linear programs are the backbone of computation and theory in mathematical
optimization. Linear optimization problems involve maximizing or minimizing
a linear function over a domain defined by a set of linear equalities and
inequalities. The simplex and primal-dual interior point methods are
currently the most computationally successful algorithms for linear
optimization. The simplex method can be viewed as a family of combinatorial
local search algorithms on the boundary of a convex polyhedron. More
precisely, the search is done over a finite graph, the skeleton of the
polyhedron, composed of the vertices and edges of the feasible region. The
search moves from a vertex of the skeleton to a neighboring one with a better
objective value, according to a chosen “pivot rule”. Today, after sixty
years of use and despite remarkable progress with competing interior point
methods, the simplex method is still widely used and remains important in
practice, particularly in combinatorial optimization and integer programming.
However, while the polynomial complexity of interior point methods has been
established, we still do not have a complete understanding of the performance
of the simplex method, in particular the number of pivots needed to go from a
starting vertex to an optimal vertex. In 1957, Hirsch conjectured that the
diameter of the skeleton defined by n inequalities in d dimensions is at most
n-d. Fifty-three years later this conjecture, this original Hirsch conjecture,
remains open. In fact, despite great effort, we still do not know whether
there is a polynomial bound on the shortest path between two vertices in the
skeleton of a polyhedron. Many authors have tried to approach this variation
of the Hirsch conjecture. The best upper bound, due to Kalai and Kleitman, is
quasi-polynomial.
The past five years have seen renewed interest and new ideas for these problems.
Recent approaches include the smoothed analysis of the simplex method, analogies
with interior point methods, explicit constructions and the systematic search
for counterexamples through computational tools, and the investigation of
combinatorial-topological abstractions of polyhedra. This workshop is devoted to
the simplex method and the Hirsch conjecture, bringing together researchers with
these various contemporary approaches.
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Confirmed Speakers
Annamaria Amenta
(University of California, Davis (UC Davis))
David Avis
(Kyoto University)
David Bremner
(University of New Brunswick)
Sergei Chubanov
(Universität-GHS Siegen)
Oliver Friedmann
(Ludwig-Maximilians-Universität München)
Komei Fukuda
(ETH Zürich)
Bernd Gärtner
(ETH Zürich)
Nicolai Hähnle
(École Polytechnique Fédérale de Lausanne (EPFL))
Fred Holt
(University of Washington)
Jonathan Kelner
(Massachusetts Institute of Technology)
Edward Kim
(Technische Universiteit te Delft)
Jim Renegar
(Cornell University)
Francisco Santos
(University of Cantabria)
Tamás Terlaky
(Lehigh University)
Santosh Vempala
(Georgia Institute of Technology)
Yinyu Ye
(Stanford University)
Günter Ziegler
(Technische Universität Berlin)
Yuriy Zinchenko
(University of Calgary)
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Contact Us:
Institute for Pure and Applied Mathematics (IPAM)
Attn: SM2011
460 Portola Plaza
Los Angeles CA 90095-7121
Phone: 310 825-4755
Fax: 310 825-4756
Email: ipam@ucla.edu
Website:
http://www.ipam.ucla.edu/programs/sm2011/
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