Big Data Analytics in Supply Chain Management: Theory and Applications

Rahimi, Iman, Gandomi, Amir H., Fong, Simon James

  • 出版商: CRC
  • 出版日期: 2024-10-04
  • 售價: $2,380
  • 貴賓價: 9.5$2,261
  • 語言: 英文
  • 頁數: 194
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 0367686287
  • ISBN-13: 9780367686284
  • 相關分類: 大數據 Big-dataData Science
  • 海外代購書籍(需單獨結帳)

相關主題

商品描述

This book discusses the results of a recent large-scale achievement on Big Data Analytics (BDA) topics among Supply Chain Management (SCM) professionals The book intends to show a diversity of supply chain management issues that may benefit from BDA, both in theory and practice.

商品描述(中文翻譯)

本書探討了最近在供應鏈管理(SCM)專業人士中關於大數據分析(BDA)主題的大規模成就結果。書中旨在展示多樣化的供應鏈管理議題,這些議題在理論和實踐上都可能受益於大數據分析。

作者簡介

Iman Rahimi, B.Sc. (Applied Mathematics), M.Sc. (Applied Mathematics - Operations Research) earned his PhD in the Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, Universiti Putra Malaysia, Malaysia in 2017. He is now a research scholar at the Faculty of Engineering &Information Technology, University of Technology Sydney, Australia. His research interests include machine learning, optimization, and supply chain management. He has edited a book entitled: "Evolutionary Computation in Scheduling" with Wiley. He has acted as an editor for journals of: "Computational Research Progress in Applied Science & Engineering (CRPASE)", "International Journal Renewable Energy Technology (IJRET)", and "International Journal of Advanced Heuristic and Meta-Heuristic Algorithms". Also, Iman has acted as an editor and co-editor of the books for some prestige publishers ("Elsevier and Taylor & Francis").

Amir H. Gandomi is a Professor of Data Science at the Faculty of Engineering & Information Technology, University of Technology Sydney. Prior to joining UTS, Prof. Gandomi was an Assistant Professor at the School of Business, Stevens Institute of Technology, USA and a distinguished research fellow in BEACON center, Michigan State University, USA. Prof. Gandomi has published over one hundred and eighty journal papers and seven books which collectively have been cited more than 16,000 times (H-index = 58). He has been named as one of the most influential scientific mind and Highly Cited Researcher (top 1%) for three consecutive years, 2017 to 2019. He also ranked 18th in GP bibliography among more than 12,000 researchers. He has served as associate editor, editor and guest editor in several prestigious journals such as AE of SWEVO, IEEE TBD, and IEEE IoTJ. Prof Gandomi is active in delivering keynotes and invited talks. His research interests are global optimisation and (big) data analytics using machine learning and evolutionary computations in particular.

Simon Fong graduated from La Trobe University, Australia, with a 1st Class Honours BEng. Computer Systems degree and a PhD. Computer Science degree in 1993 and 1998 respectively. Simon is now working as an Associate Professor at the Computer and Information Science Department of the University of Macau. He is a co-founder of the Data Analytics and Collaborative Computing Research Group in the Faculty of Science and Technology. Prior to his academic career, Simon took up various managerial and technical posts, such as systems engineer, IT consultant and e-commerce director in Australia and Asia. Dr. Fong has published over 500 international conference and peer-reviewed journal papers, mostly in the areas of data mining, data stream mining, big data analytics, meta-heuristics optimization algorithms, and their applications. He serves on the editorial boards of the Journal of Network and Computer Applications of Elsevier, IEEE IT Professional Magazine, and various special issues of SCIE-indexed journals. Simon is also an active researcher with leading positions such as Vice-chair of IEEE Computational Intelligence Society (CIS) Task Force on "Business Intelligence & Knowledge Management", and Vice-director of International Consortium for Optimization and Modelling in Science and Industry (iCOMSI).

M. Ali Ülkü, Ph.D., is a Full Professor of Supply Chain and Decision Sciences, and the Director of the Centre for Research in Sustainable Supply Chain Analytics-CRSSCA, in the Rowe School of Business at Dalhousie University, Halifax, NS, Canada. Dr. Ülkü is also cross appointed with the Department of Industrial Engineering, and the School for Resource and Environmental Studies. He received his Ph.D. in Management Sciences from the University of Waterloo, M.Sc. in Operations Research from Çukurova University, and B.Sc. in Industrial Engineering from Bilkent University. Prior to his academic career, he worked as a productivity consultant in the largest international brewery in Turkey. Dr. Ülkü's research thrusts include the theoretical modeling of sustainable supply chain and logistics systems, operations-marketing interface, and mathematical modeling of consumer behaviour and societal problems. He published in such journals as Annals of Operations Research, European Journal of Operational Research, International Journal of Production Economics, Journal of Business Research, Journal of Cleaner Production, and Service Science. His research funding includes those from The Natural Sciences and Engineering Research Council of Canada, The Scientific and Technological Research Council of Turkey, and The United States National Science Foundation. A recipient of the Exceptional Teaching Award from the University of Waterloo, Dr. Ülkü has taught operations management, business analytics, logistics, and supply chain management courses at various universities in Canada, Turkey, and the USA. He served as the Program Chair for the 2018 Canadian Operational Research Society Conference. The IEOM Society International honoured him with the 2019 Distinguished Professor Award.

作者簡介(中文翻譯)

Iman Rahimi,應用數學學士(B.Sc.)、應用數學—運籌學碩士(M.Sc.),於2017年在馬來西亞普特拉大學工程學院機械與製造工程系獲得博士學位。他目前是澳洲悉尼科技大學工程與資訊技術學院的研究學者。他的研究興趣包括機器學習、優化和供應鏈管理。他編輯了一本名為《Scheduling中的進化計算》的書籍,與Wiley出版社合作。他曾擔任以下期刊的編輯:應用科學與工程計算研究進展(CRPASE)、國際可再生能源技術期刊(IJRET)以及國際先進啟發式和元啟發式算法期刊。此外,Iman還擔任一些知名出版社(如Elsevier和Taylor & Francis)的書籍編輯和共同編輯。

Amir H. Gandomi是澳洲悉尼科技大學工程與資訊技術學院的數據科學教授。在加入UTS之前,Gandomi教授曾擔任美國史蒂文斯理工學院商學院的助理教授,以及美國密西根州立大學BEACON中心的傑出研究員。Gandomi教授已發表超過180篇期刊論文和7本書籍,這些作品的引用次數總計超過16,000次(H指數=58)。他在2017至2019年連續三年被評選為最具影響力的科學思想家和高被引研究者(前1%)。他在超過12,000名研究者中排名第18。他曾在多個知名期刊擔任副編輯、編輯和客座編輯,如SWEVO的AE、IEEE TBD和IEEE IoTJ。Gandomi教授積極參加主題演講和受邀演講。他的研究興趣主要集中在全球優化和(大)數據分析,特別是使用機器學習和進化計算。

Simon Fong於1993年和1998年分別獲得澳洲拉籌布大學一級榮譽計算機系統工程學士學位和計算機科學博士學位。Simon目前在澳門大學計算機與資訊科學系擔任副教授。他是科學與技術學院數據分析與協作計算研究小組的共同創辦人。在學術生涯之前,Simon曾在澳洲和亞洲擔任多個管理和技術職位,如系統工程師、IT顧問和電子商務總監。Fong博士已發表超過500篇國際會議和同行評審期刊論文,主要涉及數據挖掘、數據流挖掘、大數據分析、元啟發式優化算法及其應用。他擔任Elsevier的《網絡與計算機應用期刊》、IEEE IT專業雜誌及多個SCIE索引期刊特刊的編輯委員會成員。Simon還是一位活躍的研究者,擔任IEEE計算智能學會(CIS)“商業智能與知識管理”工作組的副主席,以及國際科學與工業優化與建模聯盟(iCOMSI)的副主任。

M. Ali Ülkü,博士,是加拿大哈利法克斯達爾豪斯大學Rowe商學院供應鏈與決策科學的全職教授,並擔任可持續供應鏈分析研究中心(CRSSCA)主任。Ülkü博士同時在工業工程系和資源與環境研究學院擔任交叉任職。他在滑鐵盧大學獲得管理科學博士學位,在Çukurova大學獲得運籌學碩士學位,在比爾肯特大學獲得工業工程學士學位。在學術生涯之前,他曾擔任生產力顧問。