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by Vladimir Tsurkov,A. Mironov

  • ISBN: 0792356098
  • Category: Math & Science
  • Author: Vladimir Tsurkov,A. Mironov
  • Subcategory: Mathematics
  • Other formats: mobi txt lit rtf
  • Language: English
  • Publisher: Springer; 1999 edition (April 30, 1999)
  • Pages: 310 pages
  • FB2 size: 1295 kb
  • EPUB size: 1273 kb
  • Rating: 4.6
  • Votes: 226
Download Minimax Under Transportation Constrains (Applied Optimization) fb2

Minimax Under Transportation Constrains. Transportation models are widely applied in various fields

Minimax Under Transportation Constrains. eBook 83,29 €. price for Russian Federation (gross). Transportation models are widely applied in various fields. Numerous concrete problems (for example, assignment and distribution problems, maximum-flow problem, etc. ) are formulated as trans­ portation problems. Some efficient methods have been developed for solving transportation problems of various types. This monograph is devoted to transportation problems with minimax cri­ teria. The classical (linear) transportation problem was posed several decades ago.

Автор: Vladimir Tsurkov; A. Mironov Название: Minimax Under Transportation Constrains .

Read instantly in your browser. by Vladimir Tsurkov (Author), A. Mironov (Author). ISBN-13: 978-0792356097. The 13-digit and 10-digit formats both work.

Minimax Under Transportation Constraints book. Goodreads helps you keep track of books you want to read. Start by marking Minimax Under Transportation Constraints (Applied Optimization) as Want to Read: Want to Read savin. ant to Read.

Transportation models are widely applied in various fields. In this problem, supply and demand points are given, and it is required to minimize the transportation cost

Minimax under nonlinear constraints. Article · January 2001 with 3 Reads .

Minimax under nonlinear constraints. The algorithm for solving the transportation problem in a multiterminal network with variable capacities is presented; under certain conditions, this algorithm allows one to avoid dealing with complex nonlinear large-scale problems of mathematical programming. The proposed formalism is applied to the problem of filling a network subject to constraints imposed on communication line capacities with communication flows under the condition that requests for the organization of such flows arrive to the network sequentially in time and the filling strategy must maximize the number of satisfied requests.

Vladimir Tsurkov, A. Mironov. ) are formulated as trans- portation problems. This monograph is devoted to transportation problems with minimax cri- teria.

Large-scale optimization: problems and methods. Minimax under transportation constrains. V Tsurkov, A Mironov. AA Mironov, VI Tsurkov

Large-scale optimization: problems and methods. Springer Science & Business Media, 2013. Minimax in transportation models with integral constraints: I. AA Mironov, VI Tsurkov. Journal of Computer and Systems Sciences International 42 (4), 562-574, 2003.

Minimax Under Transportation Constrains (Hardback). Vladimir Tsurkov, A. Published by Springer, Netherlands (1999). ISBN 10: 0792356098 ISBN 13: 9780792356097. Mironov Название: Minimax Under Transportation Constrains Издательство: Springer .

Transportation problems belong to the domains mathematical program­ ming and operations research. Transportation models are widely applied in various fields. Numerous concrete problems (for example, assignment and distribution problems, maximum-flow problem, etc. ) are formulated as trans­ portation problems. Some efficient methods have been developed for solving transportation problems of various types. This monograph is devoted to transportation problems with minimax cri­ teria. The classical (linear) transportation problem was posed several decades ago. In this problem, supply and demand points are given, and it is required to minimize the transportation cost. This statement paved the way for numerous extensions and generalizations. In contrast to the original statement of the problem, we consider a min­ imax rather than a minimum criterion. In particular, a matrix with the minimal largest element is sought in the class of nonnegative matrices with given sums of row and column elements. In this case, the idea behind the minimax criterion can be interpreted as follows. Suppose that the shipment time from a supply point to a demand point is proportional to the amount to be shipped. Then, the minimax is the minimal time required to transport the total amount. It is a common situation that the decision maker does not know the tariff coefficients. In other situations, they do not have any meaning at all, and neither do nonlinear tariff objective functions. In such cases, the minimax interpretation leads to an effective solution.

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