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.
Table of Contents
Convex Functions and Optimization. Dynamic Games. Multi-Objective Optimization. Hybridizing MOEAs with Mathematical-Programming Techniques. Other Decision-Making Methods. Queueing Theory. Inventory Theory. Statistical Methods. Univariate Time-Series Analysis and Forecasting: Theory and Practice. Univariate Volatility Modeling: Theory and Practice. Metaheuristic Techniques. Neural Networks. Simulation Modeling and Analysis. Web-Based Decision-Support Systems. Algorithms and Their Design. Data Envelopment Analysis: An Overview.