U: Design Methods to Enhance AI-Driven Decision Making

In the rapidly evolving landscape of industrial activities, artificial intelligence (AI) has emerged as a powerful force driving transformative change.Among its many applications, AI has proven to be instrumental in reducing processing costs associated with optimization challenges. The intersection of AI with optimization and multi-criteria decision making (MCDM) techniques has led to practical solutions in diverse fields such as manufacturing, transportation, finance, economics, and artificial intelligence. Using Traditional Design Methods to Enhance AI-Driven Decision Making delves into a wide array of topics related to optimization, decision-making, and their applications. Drawing on foundational contributions, system developments, and innovative techniques, the book explores the synergy between traditional design methods and AI-driven decision-making approaches. Offering valuable insights into leadership pathways within higher education contexts, the book presents a diverse collection of perspectives and experiences to inform readers about the complexities surrounding AI-driven decision-making. The book is ideal for higher education faculty and administrators, students of higher education, librarians, researchers, graduate students, and academicians. Contributors are invited to explore a wide range of topics, including the role of AI-driven decision-making in leadership, trends in AI-driven decision-making in Industry 5.0, applications in various industries such as manufacturing, transportation, healthcare, and banking services, as well as AI-driven optimization in mechanical engineering and materials. Additional ISBNs 9798369306406Using Traditional Design Methods to Enhance AI-Driven Decision Making is written by Nguyen Tien and published by Information Science Reference. ISBNs for Using Traditional Design Methods to Enhance AI-Driven Decision Making are 9798369306413, and the print ISBNs are 9798369306390, . Additional ISBNs include 9798369306406.