Claude Lemaréchal
| Claude Lemárechal | |
|---|---|
| File:Lemarechal.jpg
Claude Lemaréchal in 2005
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| Nationality | France |
| Fields | Mathematical optimization Operations research Scientific computing |
| Institutions | INRIA |
| Known for | Bundle methods of descent for convex minimization and nonsmooth optimization |
| Notable awards | Dantzig Prize of SIAM and MPS 1994 |
Claude Lemaréchal is a French applied mathematician.
In mathematical optimization, Claude Lemaréchal is known for his work in numerical methods for nonlinear optimization, especially for problems with nondifferentiable kinks. Lemaréchal and Phil. Wolfe pioneered bundle methods of descent for convex minimization.[1]
Claude Lemaréchal is a senior researcher (directeur de recherche) at INRIA[2] near Grenoble, France.
Contents
Awards
In 1994, Claude Lemaréchal and Roger J-B Wets were each awarded the George B. Dantzig Prize. Recognizing "original research that has had a major impact on the field of mathematical programming", the Dantzig Prize is awarded by the Society for Industrial and Applied Mathematics (SIAM) and the Mathematical Programming Society (MPS).[1]
Lagrangian duality and nonconvex primal problems
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Soon after joining INRIA (then named "IRIA"), Lemaréchal had the assignment of helping a glass-manufacturer with a problem of scheduling its production, a problem whose first formulation required minimizing a non-convex function. For this non-convex minimization problem, Lemaréchal applied the theory of Lagrangian duality that was described in Lasdon's Optimization Theory for Large Systems.[3][4] Because the primal problem was non-convex, there was no guarantee that a solution to the dual problem would provide useful information about the primal. Nonetheless, the dual problem did furnish useful information.[5] Lemaréchal's success with Lagrangian dual methods on nonlinear programming problems with nonconvexities interested Ivar Ekeland and Jean–Pierre Aubin, who applied the Shapley–Folkman lemma to explain the Lemaréchal's success.[6][7] The Aubin–Ekeland analysis of duality gaps considered the convexclosure of a nonconvex minimization problem — that is, the problem defined by the closed convex hull of the epigraph of the original problem. Following Ekeland and Aubin, similar applications of the Shapley–Folkman lemma are described in optimization monographs[7][8] and textbooks.[9] These developments were catalyzed by Lemaréchal's demonstration that Lagrangian-dual methods were useful on some optimization problems that lacked convexity.
Bundle methods of descent
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Lemaréchal's research also led to his work on (conjugate) subgradient methods and on bundle methods of descent for convex minimization problems.
Notes
- ↑ 1.0 1.1 Citation of Claude Lemaréchal for the George Dantzig Prize in 1994 in Optima, Issue 44 (1994) pages 4-5.
- ↑ INRIA is the acronym for the National Institute for Research in Computer Science and Control, in the original French, Institut national de recherche en informatique et en automatique (INRIA).
- ↑
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- ↑
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- Lemaréchal's experiments were discussed in later publications:
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- ↑ 7.0 7.1
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- ↑
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- Besides presenting Ekeland-style analysis of duality gaps (acknowledgment on page 381), Bertsekas (1982) applies Lagrangian dual methods to the scheduling of electrical power plants ("unit commitment problems"), where nonconvexity appears because of integer constraints: Lua error in package.lua at line 80: module 'strict' not found.
- ↑
- See Figure 5.1.9 (page 496): Lua error in package.lua at line 80: module 'strict' not found.
- Pages 267–279: Lua error in package.lua at line 80: module 'strict' not found.
Bibliography
Biographical
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- Citation of Claude Lemaréchal for the George Dantzig Prize in 1994 in Optima, Issue 44 (1994) pages 4–5.
Scientific publications
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