株式会社極東書店トップ > 商品一覧 > Minimax Under Transportation Constrains. Softcover reprint of the original 1st ed. 1999.
商品詳細
Minimax Under Transportation Constrains. Softcover reprint of the original 1st ed. 1999.
・ISBN 978-1-4613-6818-2 paper EUR 99.99
¥26,726.- (税込) ※(※)価格はご注文時の参考価格となります。
納品価格につきましては書籍の入荷時点で確定となります。
版元の原価改定、外国為替の変動等により異なる場合がございますので、予めご了承下さい。
お気に入り
★★★
| 著者・編者 | Tsurkov, Vladimir / Mironov, A., |
|---|---|
| シリーズ | Applied Optimization |
| 出版社 | (Springer-Verlag New York Inc., US) |
| 出版年月 | 2013 |
| ページ数 | 310 pp. |
| 言語 | ENG |
| ニュース番号 | <M25-17767> |
解説
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.