Hierarchical Decision Making in Stochastic Manufacturing Systems

Name: Hierarchical Decision Making in Stochastic Manufacturing Systems
Brand: Springer-Verlag New York Inc.
SKU: 9781461266945
Price: 105.5 EUR
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Автор: Suresh P. Sethi, Qing Zhang

Език:

Корици: С меки корици

Издател: Springer-Verlag New York Inc.

Наличност: Външен склад

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One of the most important methods in dealing with the optimization of large, complex systems is that...

Информация за книгата

Автор

Suresh P. Sethi, Qing Zhang

Език

Английски език

Корици

Книга - С меки корици

Издадена

2012

страници

422

EAN

9781461266945

ISBN

1461266947

Enbook ID

06794873

Издател

Springer-Verlag New York Inc.

Теглоt

670

Размери

155 x 235 x 24

Пълно описание

One of the most important methods in dealing with the optimization of large, complex systems is that of hierarchical decomposition. The idea is to reduce the overall complex problem into manageable approximate problems or subproblems, to solve these problems, and to construct a solution of the original problem from the solutions of these simpler prob lems. Development of such approaches for large complex systems has been identified as a particularly fruitful area by the Committee on the Next Decade in Operations Research (1988) [42] as well as by the Panel on Future Directions in Control Theory (1988) [65]. Most manufacturing firms are complex systems characterized by sev eral decision subsystems, such as finance, personnel, marketing, and op erations. They may have several plants and warehouses and a wide variety of machines and equipment devoted to producing a large number of different products. Moreover, they are subject to deterministic as well as stochastic discrete events, such as purchasing new equipment, hiring and layoff of personnel, and machine setups, failures, and repairs.

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Hierarchical Decision Making in Stochastic Manufacturing Systems

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