Managerial activities have become complex and it is necessary to make right decisions to avoid heavy losses. Whether it is a manufacturing unit, or a service organization, the resources have to be utilized to its maximum in an efficient manner. In such situations, there is a greater need for applying scientific methods for decision-making to increase the probability of coming up with good decisions. Quantitative analysis is a scientific approach to managerial decision-making. The successful use of quantitative techniques would help the organization in solving complex problems on time, with greater accuracy and in the most economical way. This book elaborates a variety of these techniques with relevant contextual real life problem areas.
This book focuses on the need to demystify the subject and makes it easy for students to grasp the principles and details involved. It has been written in an easy and understandable manner, specifically for the beginners exposed to the subject for the first time. Hence, it addresses specific requirements that lead to a good knowledge about the subject. An attempt has also been made to explain things in a logical progression, in the simplest possible way, so that neophytes may quickly grasp the concepts and methodology.
A novel approach in the book is the illustrative use of computers with TORA package, as a problem-solving tool. This will create awareness among the students about the enormous problem-solving solutions through computers and also help compare the results that are worked-out manually. It is hoped that the readers will benefit enormously and develop a better insight and knowledge on the subject matter.
About the book:
Linear Programming: Formulation and Graphical Method; Linear Programming: Analytical Methods; Transportation Model; Assignment Model; Network Analysis PERT/CPM; Sequencing; Replacement Models; Queuing Theory; Game Theory; Simulation
- Publisher: Excel books
- Product Code: 978-81-7446-880-2
- Availability: 20
- INR 695.00
- Excluding Tax: INR 555.00
Tags: Operations Research