Application of Advanced Optimization Techniques for Healthcare Analytics

Application of Advanced Optimization Techniques for Healthcare Analytics, 1st Edition, is an excellent compilation of current and advanced optimization techniques which can readily be applied to solve different hospital management problems. The healthcare system is currently a topic of significant investigation to make life easier for those who are disabled, old, or sick, as well as for young children. The emphasis of the healthcare system has evolved throughout time due to several emerging beneficial technologies, such as personal digital assistants (PDAs), data mining, the internet of things, metaheuristics, fog computing, and cloud computing.

Metaheuristics are strong technology for tackling several optimization problems in various fields, especially healthcare systems. The primary advantage of metaheuristic algorithms is their ability to find a better solution to a healthcare problem and their ability to consume as little time as possible. In addition, metaheuristics are more flexible compared to several other optimization techniques. These algorithms are not related to a specific optimization problem but could be applied to any optimization problem by making some small adaptations to become suitable to tackle it.

The successful outcome of this book will enable a decision-maker or practitioner to pick a suitable optimization approach when making decisions to schedule patients under crowding environments with minimized human errors.

《高級優化技術在醫療分析中的應用，第一版》是一本優秀的彙編，收錄了目前和先進的優化技術，這些技術可以直接應用於解決不同的醫院管理問題。醫療系統目前是一個重要的研究主題，旨在為殘疾人、老年人、病人以及年幼的兒童提供更便利的生活。醫療系統的重點隨著時間的推移而演變，這歸因於一些新興的有益技術，如個人數字助手（PDA）、數據挖掘、物聯網、元啟發式算法、雲計算等。

元啟發式算法是解決各個領域特別是醫療系統中多個優化問題的強大技術。元啟發式算法的主要優勢在於能夠找到更好的醫療問題解決方案，並且能夠在最短的時間內完成。此外，與其他幾種優化技術相比，元啟發式算法更具靈活性。這些算法與特定的優化問題無關，但可以通過進行一些小的調整來應用於任何優化問題。

本書的成功成果將使決策者或從業人員能夠在擁擠環境下安排患者並減少人為錯誤時，選擇合適的優化方法。

MOHAMED ABDEL-BASSET (Senior Member, IEEE) received the BSc, MSc, and Ph.D degrees in operations research from the Faculty of Computers and Informatics, Zagazig University, Egypt. He is currently an Associate Professor with the Faculty of Computers and Informatics, Zagazig University. He has published more than 200 articles in international journals and conference proceedings. He is working on the application of multi-objective and robust metaheuristic optimization techniques. His current research interests include optimization, operations research, data mining, computational intelligence, applied statistics, decision support systems, robust optimization, engineering optimization, multi-objective optimization, swarm intelligence, evolutionary algorithms, and artificial neural networks. He is an editor and a reviewer of different international journals and conferences.

RIPON K. CHAKRABORTTY (Senior Member, IEEE) is the Program Coordinator for Master of Decision Analytics and Master of Engineering Science Programs, and the team leader of 'Decision Support & Analytics Research Group' at the School of Engineering & Information Technology, UNW Canberra, Australia. He obtained his Ph.D from the same University in 2017 while completing his MSc and BSc from Bangladesh University of Engineering & Technology in Industrial & Production Engineering in 2013 and 2009, respectively. He has written four book chapters and over 170 technical journal and conference papers. His research interest covers a wide range of topics in operations research, project management, supply chain management, artificial intelligence, and information systems management. Many organizations have funded his research program, such as the Department of Defence, Commonwealth Government, Australia. He is an associate editor and a reviewer of different international journals and conferences.

REDA MOHAMED received his BSc degree from the Department of Computer Science, Faculty of Computers and Informatics, Zagazig University, Egypt. He is working on the application of multi-objective and robust metaheuristic optimization techniques in computational intelligence. His research interests include robust optimization, multi-objective optimization, swarm intelligence, evolutionary algorithms, and artificial neural networks.

MOHAMED ABDEL-BASSET（IEEE高級會員）在埃及Zagazig大學計算機與資訊學院獲得了運籌學的學士、碩士和博士學位。他目前是Zagazig大學計算機與資訊學院的副教授。他在國際期刊和會議論文中發表了200多篇文章。他的研究方向包括多目標和魯棒元啟發式優化技術的應用。他目前的研究興趣包括優化、運籌學、數據挖掘、計算智能、應用統計、決策支持系統、魯棒優化、工程優化、多目標優化、群體智能、演化算法和人工神經網絡。他是不同國際期刊和會議的編輯和審稿人。

RIPON K. CHAKRABORTTY（IEEE高級會員）是澳大利亞UNW坎培拉校區工程與資訊技術學院的碩士決策分析和碩士工程科學課程的計劃協調員，也是“決策支持與分析研究小組”的團隊負責人。他在2017年獲得了該大學的博士學位，並在2013年和2009年分別在孟加拉國工程與技術大學獲得了工業與生產工程的碩士和學士學位。他撰寫了四章書籍章節和超過170篇技術期刊和會議論文。他的研究興趣涵蓋了運籌學、項目管理、供應鏈管理、人工智能和信息系統管理等各個領域。許多組織都對他的研究項目提供了資金支持，例如澳大利亞國防部和聯邦政府。他是不同國際期刊和會議的副編輯和審稿人。

REDA MOHAMED在埃及Zagazig大學計算機與資訊學院的計算機科學系獲得了學士學位。他致力於在計算智能領域應用多目標和魯棒元啟發式優化技術。他的研究興趣包括魯棒優化、多目標優化、群體智能、演化算法和人工神經網絡。