Introductory Management Science
Prentice-Hall (Publisher)
Published on 1. December 1992
Book
Paperback/Softback
880 pages
978-0-13-503582-5 (ISBN)
Article exhausted; check for reprint
Description
Addressing the needs of both management students and those heading for a career in business administration, this text emphasises the role of management science techniques in the larger context of business decision-making. Strong emphasis on models is included - how they are created, used and the insights they provide - and the importance of management judgement in utilizing the informationn provided. Examples and end of chapter case studies give detailed examples of how techniques are utilized in practice, and thorough integration of computer applications is made, including the use of many popular software packages such as Lotus 1-2-3, @RISK, LINDO and QSB+. New computer examples and problems for spreadsheets and @RISK have been added to most of the chapters in Part II.
More details
Edition
International 2 Revised ed
Language
English
Place of publication
Harlow
United Kingdom
Publishing group
Pearson Education Limited
Target group
College/higher education
Professional and scholarly
Illustrations
Illustrations
Dimensions
Height: 277 mm
Width: 210 mm
Weight
1812 gr
ISBN-13
978-0-13-503582-5 (9780135035825)
Copyright in bibliographic data is held by Nielsen Book Services Limited or its licensors: all rights reserved.
Schweitzer Classification
Other editions
New editions

Jeffrey H. Moore | Larry R. Weatherford
Decision Modeling with Microsoft (R) Excel
United States Edition
Book
01/2001
6th Edition
Pearson
€122.86
Article exhausted; check for reprint
Persons
Author
University of Alabama, USA
Revised by
Content
Part 1 Deterministic models; linear programming - formal and spreadsheet models; linear programming - geometric representations and graphical solutions; analysis of LP models - the graphical approach; linear programs - computer analysis, interpreting sensitivity output and the dual problem; linear programming - the simple method; linear programming - special applications; integer and quadratic programming; network models; inventory control with known demand; heuristics, multiple objectives and goal programming; calculus-based optimization and introduction to non-linear programming. Part 2 Probabilistic models: simulation; decision theory and decision trees; project management - PERT and CPM; inventory models with probabilistic demand; queuing models; forecasting.