Nonlinear discrete optimization : an algorithmic theory / Shmuel Onn.

By: Material type: TextSeries: Zurich lectures in advanced mathematicsPublication details: Zürich, Switzerland : European Mathematical Society Publishing House, c2010.Description: x, 137 : ill. (some col.) ; 24 cmISBN:
  • 9783037190937 (pbk.)
  • 3037190930 (pbk.)
Subject(s): LOC classification:
  • QA402.5 .O56 2010
Summary: This monograph develops an algorithmic theory of nonlinear discrete optimization. It introduces a simple and useful setup which enables the polynomial time solution of broad fundamental classes of nonlinear combinatorial optimization and integer programming problems in variable dimension. An important part of this theory is enhanced by recent developments in the algebra of Graver bases. The power of the theory is demonstrated by deriving the first polynomial time algorithms in a variety of application areas within operations research and statistics, including vector partitioning, matroid optimization, experimental design, multicommodity flows, multi-index transportation and privacy in statistical databases. --Book Jacket.
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Item type Current library Call number Copy number Status Barcode
Book Institute of Mathematics Library QA402.5.O56 2010 (Browse shelf(Opens below)) 1 Not For Loan 3319

Includes bibliographical references (p. [129]-134) and index.

This monograph develops an algorithmic theory of nonlinear discrete optimization. It introduces a simple and useful setup which enables the polynomial time solution of broad fundamental classes of nonlinear combinatorial optimization and integer programming problems in variable dimension. An important part of this theory is enhanced by recent developments in the algebra of Graver bases. The power of the theory is demonstrated by deriving the first polynomial time algorithms in a variety of application areas within operations research and statistics, including vector partitioning, matroid optimization, experimental design, multicommodity flows, multi-index transportation and privacy in statistical databases. --Book Jacket.

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