Operations Research and Data Analytics: Current Trends and Future Perspectives : Selected Papers from International Conference on Industrial Engineering and Analytics (ICONIEA) 2024 (Lecture Notes on Multidisciplinary Industrial Engineering)

  • 予約

Operations Research and Data Analytics: Current Trends and Future Perspectives : Selected Papers from International Conference on Industrial Engineering and Analytics (ICONIEA) 2024 (Lecture Notes on Multidisciplinary Industrial Engineering)

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  • 製本 Hardcover:ハードカバー版/ページ数 200 p.
  • 言語 ENG
  • 商品コード 9789819683260

Full Description

This book, "Operations Research and Data Analytics: Current Trends and Future Perspectives", presents 25 peer reviewed articles from the International Conference on Industrial Engineering & Analytics (ICONIEA 2024), organized by the Department of Industrial and Systems Engineering at IIT Kharagpur, India. This compilation of articles aims to provide insights into how Operations Research (OR) and Data Analytics (DA) are used to solve real-world decision problems in business, transportation, healthcare, agriculture, climate science, safety, security, and surveillance.
 
The book is organized into five thematic sections that represent the significant ways ORDA are reshaping industries and scientific research. Part I focuses on importance of decision sciences and business analytics in industry. Part II covers the implementation of OR in transportation and logistics sector. Part III explores application of analytics in healthcare. Part IV explains the role of ORDA techniques in agricultural and climate sciences, and Part V examines application of ORDA in safety, security, and surveillance.

Contents

Data-Centric Prognostics: Challenges and Opportunities in the Era of Industry 4.0.- Customer Segmentation of First-Time Home Buyers Movers for Marketing.- Quantification of Customer Experience in Retail Banking.- Challenging the Dynamics of Time: Evaluating Real-World based Time Series Data Generation.- Revolutionizing Sales Forecasting in Quick-Service Restaurants using Hybrid Deep Learning Models.

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