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Full Description
Operational research (OR) methods are used in many fields of sciences like computer engineering, industrial engineering, social works, business management, medical studies and finance. This book, is the second book in the series of Operational Research (OR) books. It brings together the latest advances of these methods written by experts from all over the world. The book comprises 13 chapters and is split into four main parts, i.e., OR in supply chain management, OR in production planning and inventory management, OR in signal processing and OR in social sciences.
The book contains recent methodologies and comprehensive reviews where necessary, so that readers can follow up to date progress in the field while observing various applications with large datasets. The data used in the book is available in public databases. Therefore, the reader can easily access them and try their own approaches for comparison. Furthermore, since the book covers the literature reviews in each chapter, readers can both follow other benchmark techniques in the field and learn the theoretical aspects of the selected methods. In conclusion, the book will be assist in the discovery of new avenues for novel researchers who are interested in OR methods.
Contents
Preface. PART I: OPERATION RESEARCH IN SUPPLY CHAIN MANAGEMENT. 1. A Bibliometric and Descriptive Review of Mathematical Models for Vulnerable and Resilient Supply Chain Management. 2. Operational Optimization of Vectors for Logical Networks. 3. Application of Various Modelling Techniques into Consumer Confidence Index. PART II: OPERATION RESEARCH IN PRODUCTION PLANNING AND INVENTORY MANAGEMENT. 4. Optimization and Computing Using Intelligent Data-Driven Approaches for Decision-Making. 5. Aggregate Production Planning: A Novel Game Model. 6. Balancing Cooperation and Competition in Game Theory for Business. PART III: OPERATION RESEARCH IN SIGNAL PROCESSING. 7. Pixel-based Snow Cover Classification over Complex Mountainous Regions by Random Forest Algorithm. 8. Construction of a Circular Graphical Network via an RNA-seq Data Set. 9. Imputation of Missing Value in EMG Signaling Data. 10. The Application of the R-Vine Copula and Different Regression Models in the Inference of Hodgkin-Huxley Data. PART IV: OPERATION RESEARCH IN SOCIAL SCIENCES. 11. Who Trusts Which Type of Artificial Intelligence? 12. A Comparison of Desirability Functions on a Multi-response Optimization Problem. 13. Statistical Modeling of Social Data: A Case Study from TAYA 2016 Survey. Index.
