Last edited by Shaktinos
Sunday, July 19, 2020 | History

1 edition of Hierarchical Decision Making in Stochastic Manufacturing Systems found in the catalog.

Hierarchical Decision Making in Stochastic Manufacturing Systems

by Suresh P. Sethi

  • 40 Want to read
  • 25 Currently reading

Published by Birkhäuser Boston, Imprint, Birkhäuser in Boston, MA .
Written in English


Edition Notes

Statementby Suresh P. Sethi, Qing Zhang
SeriesSystems & Control: Foundations & Applications, Systems & control
ContributionsZhang, Qing
The Physical Object
Format[electronic resource] /
Pagination1 online resource (419 pages).
Number of Pages419
ID Numbers
Open LibraryOL27043387M
ISBN 10146120285X
ISBN 109781461202851
OCLC/WorldCa840277771

Stochastic Models of Manufacturing Systems Ivo Adan Tuesday April 2/47 Modeling and analysis of manufacturing systems: –Single-stage systems –Multi-stage flow lines –Job-shop systems Decision making Modeling. 6/47 Tuesday April 21 Some issues: Complexity versus Simplicity FlexibilityFile Size: 3MB. evaluation of the hierarchical controls approach by com-paring hierarchical controls to the optimal solutions (when possible) and to the solutions obtained by other heuristic approaches published in the literature. For this purpose, we select manufacturing systems with two failure-prone machines in tandem with an objective of minimizing a con-.

  Most manufacturing systems are large, complex, and operate in an environment of uncertainty. It is common practice to manage such systems in a hierarchical fashion. This book articulates a new theory that shows that hierarchical decision making can in fact lead to a near optimization of system goals.4/5(1). This paper is concerned with near-optimal control of manufacturing systems consisting of two unreliable machines in tandem and having the objective of minimizing the total discounCited by:

We close this gap by developing a multi-criteria decision support system for robust outsourcing decision-making in stochastic manufacturing systems that combines DEA with aggregate production planning. Previous work entails a similar approach that has been developed in an R&D portfolio context by Vandaele and Decouttere (). by: In their book, Sethi and Zhang () focused on hierarchical decision-making in stochastic manufacturing systems. Different hierarchical levels have different time scales associated with their decisions. Hierarchy is discussed from a temporal perspective, but organizational interactions across hierarchies are not explicitly modeled.


Share this book
You might also like
HOW TO BECOME A BISHOP WITHOUT BEING RELIGIOUS

HOW TO BECOME A BISHOP WITHOUT BEING RELIGIOUS

Polonia

Polonia

Still midnight

Still midnight

The green studio handbook

The green studio handbook

Quaker studies.

Quaker studies.

Manufacturing policy

Manufacturing policy

Christianity and the Roman government

Christianity and the Roman government

A Sudden Outbreak of Common Sense

A Sudden Outbreak of Common Sense

Spotlight Christmas Prepack 38 (Carton Pack)

Spotlight Christmas Prepack 38 (Carton Pack)

On our way rejoicing

On our way rejoicing

My adventures and researches in the Pacific

My adventures and researches in the Pacific

tobacco kingdom

tobacco kingdom

adventures of Gil Blas of Santillane

adventures of Gil Blas of Santillane

Laxtons building price book.

Laxtons building price book.

The Dynamics of the Dispersed City

The Dynamics of the Dispersed City

Problem Solving With the Computer

Problem Solving With the Computer

Hierarchical Decision Making in Stochastic Manufacturing Systems by Suresh P. Sethi Download PDF EPUB FB2

Hierarchical Decision Making in Stochastic Manufacturing Systems (Systems & Control: Foundations & Applications) [Sethi, Suresh P., Zhang, Qing] on *FREE* shipping on qualifying offers.

Hierarchical Decision Making in Stochastic Manufacturing Systems (Systems & Control: Foundations & Applications)Format: Hardcover. Hierarchical Decision Making in Stochastic Manufacturing Systems.

Authors: Sethi, Suresh P., Zhang, Qing Free Preview. 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.

Get this from a library. Hierarchical decision making in stochastic manufacturing systems. [Suresh P Sethi; Qing Zhang]. Get this from a library. Hierarchical Decision Making in Stochastic Manufacturing Systems. [Suresh P Sethi; Qing Zhang] -- 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. Expounds a new theory of hierarchical decision making to improve the management of large and complex manufacturing systems to near optimization.

The key to the approach is recognizing that events happen on different time scales; for example, the breakdown and repair of production equipment happens much more often than changes in product : $ Book Reviews Hierarchical Decision Making in Stochastic Manufacturing Systems, by Suresh P.

SETHI and Qing ZHANG; Birkh/tuser-Verlag; Boston, MA, USA; ; pp.; $; ISBN: Reviewed by: Jacek B. KRAWCZYK Victoria University of Wellington, New Zealand This is a comprehensive monograph on the application of control theory to stochastic.

Multilevel Hierarchical Decision Making in Stochastic Marketing-Production Systems Article in SIAM Journal on Control and Optimization 33(2) February.

Hierarchical Decision Making in Stochastic Manufacturing Systems Suresh P. Sethi FRSC, Qing Zhang (auth.) One of the most important methods in dealing with the optimization of large, complex systems is that of hierarchical decomposition.

Most manufacturing firms are large, complex systems characterized by several decision subsystems, such as finance, personnel, marketing, and operations. They may have a number of plants and warehouses and produce a large number of different products using a wide variety of machines and : Suresh P.

Sethi, Qing Zhang. () Hierarchical capacity expansion and production planning decisions in stochastic manufacturing systems.

Journal of Operations Management() Multilevel hierarchical open-loop and feedback controls in Cited by: Hierarchical Decision Making in Stochastic Manufacturing Systems by Suresh P Sethi starting at $ Hierarchical Decision Making in Stochastic Manufacturing Systems has 2 available editions to buy at Half Price Books Marketplace.

This paper presents an asymptotic analysis of hierarchical marketing-production systems with stochastic demand and stochastic production capacity modelled as finite state Markov processes. The decision variables used are advertising and production rates which influence capacity, demand, and inventory levels.

The objective of this paper is to maximize Cited by: : Average-Cost Control of Stochastic Manufacturing Systems (Stochastic Modelling and Applied Probability) (): Suresh P.

Sethi, Han-Qin Zhang, Qing Zhang: BooksCited by: "Hierarchical Decision Making in Stochastic Manufacturing Systems: S.P. Sethi and Qing Zhang, (Birkhauser, Boston, Cambridge, MA) ISBN ," Journal of Economic Dynamics and Control, Elsevier, vol.

21(10), pagesAugust. Circulant Preconditioners for Markov-Modulated Poisson Processes and Their Applications to Manufacturing Systems SIAM Journal on Matrix Analysis and Applications, Vol. 18, No. 2 Hierarchical production controls in a stochastic two-machine flowshop with a finite internal bufferCited by: Most manufacturing systems are large, complex, and operate in an environment of uncertainty.

It is common practice to manage such systems in a hierarchical fashion. This book articulates a new theory that shows that hierarchical decision making can in fact lead to a near optimization of system goals. The material in the book cuts across disciplines. It will appeal to. Most manufacturing systems are large, complex, and operate in an environment of uncertainty.

It is common practice to manage such systems in a hierarchical fashion. This book articulates a new theory that shows that hierarchical decision making can in. Manufacturing Systems Engineering [Book Reviews] Hierarchical Decision Making in Stochastic Manufacturing Systems performance evaluation of automated manufacturing systems.

The book is the. This book articulates a new theory that shows that hierarchical decision making can in fact lead to a near optimization of system goals. The material in the book cuts across disciplines. It will appeal to graduate students and researchers in applied mathematics, operations management, operations research, and system and control : $.

Suresh P. Sethi identified such indifference points for the first time in Hierarchical manufacturing systems. Most manufacturing systems are large, complex, and subject to uncertainty.

The problem of the efficient management of such systems is of critical importance to a nation's economic mater: Carnegie Mellon University. (Book by Sethi, Suresh P., Thompson, Gerald L.) (Hierarchical Decision Making in Stochastic Manufacturing Systems) Author: Suresh P. Sethi Dec (Optimal Consumption and Investment with Bankruptcy) Author: Suresh P.

Sethi Nov; Hierarchical Decision Making in Stochastic Manufacturing Systems; Membership.Buy (ebook) Hierarchical Decision Making in Stochastic Manufacturing Systems by Qing Zhang, Suresh P.

Sethi, eBook format, from the Dymocks online bookstore.