Quantitative Techniques For Decision Making

Quantitative Techniques For Decision Making

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Product Specifications

Publisher PHI Learning All Industrial Engineering books by PHI Learning
ISBN 9788120342781
Author: M. P. Gupta, R. B. Khanna
Number of Pages 772
Available in all digital devices
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This thoroughly revised and well-received book, now in its Fourth Edition, continues to give an in-depth and incisive analysis of the various mathematical techniques required for managers in their decision-making process. The book provides a clear understanding of the practical utility of mathematical modelling and techniques, such as linear programming, integer programming, goal programming, dynamic programming, inventory models, decision theory, game theory, network analysis, queuing, simulation and Markov analysis, for solving real-life problems. The book lays emphasis on the practical applications of the techniques rather than their rigorous mathematical treatment. It also discusses probability and probability distributions—essential to tackling the everyday uncertainties of life.

The book is primarily intended as a textbook for undergraduate and postgraduate students of management, postgraduate students of commerce, students of Master of Financial Control (MFC) course, and undergraduate students of industrial and production engineering. In addition, practising managers will also find the book immensely helpful in their day-to-day decision-making process.

New to This Edition :

A section describing the construction of activity on node (AON) networks for CPM and PERT networks has been included considering that most software designed for network analysis plot networks in this format.

An appendix on ‘Mathematics for Managers’ which includes the topics of Matrix Algebra and Differential Calculus.

New solved and unsolved problems.



Preface to the First Edition.

1. Decision Making: A Quantitative Approach.

2. Linear Programming: Graphic Method. 

3. Linear Programming: Simplex Method.

4. Transportation Model.

5. Assignment Model.

6. Integer Programming.

7. Goal Programming.

8. Dynamic Programming.

9. Probability.

10. Probability Distributions.

11. Inventory Models.

12. Replacement Models.

13. Network Models: CPM and PERT.

14. Decision Theory.

15. Theory of Games.

16. Sequencing.

17. Queuing Theory.

18. Simulation.

19. Markov Analysis.


A: Mathematics for Managers.

B: Standard Normal Probability Distribution.

C. Values of e– for Computing Poisson Probabilities.

D. Table of Random Numbers.


Answers to Concept Quiz.

Answers to Selected Questions.


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