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Mathematical Programming

, Volume 169, Issue 1, pp 1–4 | Cite as

Preface

  • Hoai An Le Thi
  • Tao Pham Dinh
Preface Series B
  • 146 Downloads

Mathematical optimization experienced, from both theoretical and algorithmic points of view, two key evolutions. The first one related to the introduction of linear programming and, above all, the discovery of the simplex algorithm by Dantzig in 1948. Whereas the logical and natural extension of linear programming to convex analysis and convex programming—which offered a wide boulevard to the theory, algorithms and applications of this rich research field—concretized this second evolution. Due to its geometrical feature, convex analysis was quite inspiring and facilitating statements of its major results. From 1952 to 1984, smooth/nonsmooth convex programming were extensively developed and most of their theoretical and algorithmic tools were established. The 1985–1990 period was mainly devoted to their applications for modeling/solving large-scale real-world convex programs from different fields of applied sciences. Existing algorithms were thus well adapted to specific structures of...

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© Springer-Verlag GmbH Germany, part of Springer Nature and Mathematical Optimization Society 2018

Authors and Affiliations

  1. 1.Laboratory of Theoretical and Applied Computer Science (LITA)University of LorraineMetz TechnopoleFrance
  2. 2.Laboratory of MathematicsNational Institute for Applied Sciences - RouenSaint-Étienne-du-Rouvray CedexFrance

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