Decision Sciences Theory and Practice 1st Edition by Raghu Nandan Sengupta, Aparna Gupta, Joydeep Dutta ISBN 131518317X 9781466564305

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ISBN 10: 131518317X 
ISBN 13: 9781466564305
Author: Raghu Nandan Sengupta, Aparna Gupta, Joydeep Dutta

This handbook is an endeavour to cover many current, relevant, and essential topics related to decision sciences in a scientific manner. Using this handbook, graduate students, researchers, as well as practitioners from engineering, statistics, sociology, economics, etc. will find a new and refreshing paradigm shift as to how these topics can be put to use beneficially. Starting from the basics to advanced concepts, authors hope to make the readers well aware of the different theoretical and practical ideas, which are the focus of study in decision sciences nowadays. It includes an excellent bibliography/reference/journal list, information about a variety of datasets, illustrated pseudo-codes, and discussion of future trends in research. Covering topics ranging from optimization, networks and games, multi-objective optimization, inventory theory, statistical methods, artificial neural networks, times series analysis, simulation modeling, decision support system, data envelopment analysis, queueing theory, etc., this reference book is an attempt to make this area more meaningful for varied readers. Noteworthy features of this handbook are in-depth coverage of different topics, solved practical examples, unique datasets for a variety of examples in the areas of decision sciences, in-depth analysis of problems through colored charts, 3D diagrams, and discussions about software.

Decision Sciences Theory and Practice 1st Table of contents:

1. Convex Functions in Optimization
2. Introduction to Game Theory
3. Multi-Objective Optimization
4. Hybridizing MOEAs with Mathematical-Programming Techniques
5. Other Decision-Making Models
6. Queueing Theory
7. Inventory Theory
8. Statistical Methods
9. Univariate Time-Series Analysis and Forecasting: Theory and Practice
10. Univariate Volatility Modeling: Theory and Practice
11. Metaheuristic Techniques
12. Neural Networks
13. Simulation Modeling and Analysis
14. Web-Enabled Decision-Support Systems
15. Algorithms and Their Design
16. Data Envelopment Analysis: An Overview

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