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Titlebook: Linear Programming in Industry; Theory and Applicati Sven Dan? Book 19601st edition Springer-Verlag Wien 1960 algebra.algorithms.engineer.m

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書目名稱Linear Programming in Industry
副標(biāo)題Theory and Applicati
編輯Sven Dan?
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圖書封面Titlebook: Linear Programming in Industry; Theory and Applicati Sven Dan? Book 19601st edition Springer-Verlag Wien 1960 algebra.algorithms.engineer.m
描述The present volume is intended to serve a twofold purpose. First, it provides a university text of Linear Programming for students of or operations research interested in the theory of production economics and cost and its practical applications; secondly, it is the author‘s hope that engineers, business executives, managers, and others responsible for the organization and planning of industrial operations may find the book useful as an introduction to Linear Programming methods and techniques. Despite the different backgrounds of these categories of potential readers, their respective fields overlap to a considerable extent; both are concerned with economic optimization problems, and the use of Linear Programming to problems of production planning is simply applied theory of production. The non-economist reader may, but should not, pass over Chapter IV in which the linear production model is linked up with the economic theory of production. Without being an advanced text, the book aims at covering enough ground to make the reader capable of detecting, formulating, and solving such linear planning problems as he may encounter within his particular field. No heavy demands are made o
出版日期Book 19601st edition
關(guān)鍵詞algebra; algorithms; engineer; model; operations research; optimization; organization; planning; production;
版次1
doihttps://doi.org/10.1007/978-3-7091-3644-7
isbn_ebook978-3-7091-3644-7
copyrightSpringer-Verlag Wien 1960
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Duality in Linear Programming,Linear programming models possess the interesting property of forming pairs of symmetrical problems. To any maximization problem corresponds a minimization problem involving the same data, and there is a close correspondence between their optimal solutions. The two problems are said to be “.”of each other.
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Computational Procedures for Solving Linear Programming Problems,the simplex criterion, we move to a neighboring basis by replacing one of the basic variables, and so forth, until a basic feasible solution is attained in which all of the simplex coefficients are non-positive (in a minimization problem, non-negative). By the Fundamental Theorem, such a solution will be an optimal solution.
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