The large and complex challenges the world is facing, the growing prevalence of huge data sets, and the new and developing ways for addressing them (artificial intelligence, data science, machine learning, etc.), means it is increasingly vital that academics and professionals from across disciplines have a basic understanding of the mathematical underpinnings of effective, optimized decision-making. Without it, decision makers risk being overtaken by those who better understand the models and methods, that can best inform strategic and tactical decisions.
Introduction to Optimization-Based Decision-Making provides an elementary and self-contained introduction to the basic concepts involved in making decisions in an optimization-based environment. The mathematical level of the text is directed to the post-secondary reader, or university students in the initial years. The prerequisites are therefore minimal, and necessary mathematical tools are provided as needed. This lean approach is complemented with a problem-based orientation and a methodology of generalization/reduction. In this way, the book can be useful for students from STEM fields, economics and enterprise sciences, social sciences and humanities, as well as for the general reader interested in multi/trans-disciplinary approaches.
Features
"synopsis" may belong to another edition of this title.
João Luís de Miranda is Professor at ESTG-Escola Superior de Tecnologia e Gestão (IPPortalegre) and Researcher in Optimization methods and Process Systems Engineering (PSE) at CERENA-Centro de Recursos Naturais e Ambiente (IST/ULisboa). He has been teaching for more than twenty years in the field of Mathematics (e.g., Calculus, Operations Research-OR, Management Science-MS, Numerical Methods, Quantitative Methods, Statistics) and has authored/edited several publications in Optimization, PSE, and Education subjects in Engineering and OR/MS contexts. João Luís de Miranda is addressing the research subjects through international cooperation in multidisciplinary frameworks, and is serving on several boards/committees at national and European level.
"About this title" may belong to another edition of this title.
FREE shipping within United Kingdom
Destination, rates & speedsSeller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: As New. Unread book in perfect condition. Seller Inventory # 47618295
Quantity: Over 20 available
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Condition: New. Seller Inventory # 47618295-n
Quantity: Over 20 available
Seller: THE SAINT BOOKSTORE, Southport, United Kingdom
Paperback / softback. Condition: New. New copy - Usually dispatched within 4 working days. 453. Seller Inventory # B9781032119779
Quantity: 1 available
Seller: Majestic Books, Hounslow, United Kingdom
Condition: New. Seller Inventory # 398680392
Quantity: 3 available
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Condition: New. In. Seller Inventory # ria9781032119779_new
Quantity: Over 20 available
Seller: PBShop.store UK, Fairford, GLOS, United Kingdom
PAP. Condition: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9781032119779
Quantity: Over 20 available
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 241 pages. 6.00x0.56x9.00 inches. In Stock. This item is printed on demand. Seller Inventory # __1032119772
Quantity: 1 available
Seller: CitiRetail, Stevenage, United Kingdom
Paperback. Condition: new. Paperback. The large and complex challenges the world is facing, the growing prevalence of huge data sets, and the new and developing ways for addressing them (artificial intelligence, data science, machine learning, etc.), means it is increasingly vital that academics and professionals from across disciplines have a basic understanding of the mathematical underpinnings of effective, optimized decision-making. Without it, decision makers risk being overtaken by those who better understand the models and methods, that can best inform strategic and tactical decisions.Introduction to Optimization-Based Decision-Making provides an elementary and self-contained introduction to the basic concepts involved in making decisions in an optimization-based environment. The mathematical level of the text is directed to the post-secondary reader, or university students in the initial years. The prerequisites are therefore minimal, and necessary mathematical tools are provided as needed. This lean approach is complemented with a problem-based orientation and a methodology of generalization/reduction. In this way, the book can be useful for students from STEM fields, economics and enterprise sciences, social sciences and humanities, as well as for the general reader interested in multi/trans-disciplinary approaches.Features Collects and discusses the ideas underpinning decision-making through optimization tools in a simple and straightforward manner Suitable for an undergraduate course in optimization-based decision-making, or as a supplementary resource for courses in operations research and management science Self-contained coverage of traditional and more modern optimization models, while not requiring a previous background in decision theory This book provides an elementary and self-contained introduction to the basic concepts involved in making decisions in an optimization-based environment. The mathematical level of the text is directed to the post-secondary reader, or university students in the initial years. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Seller Inventory # 9781032119779
Quantity: 1 available
Seller: PBShop.store US, Wood Dale, IL, U.S.A.
PAP. Condition: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000. Seller Inventory # L0-9781032119779
Quantity: Over 20 available
Seller: GreatBookPrices, Columbia, MD, U.S.A.
Condition: As New. Unread book in perfect condition. Seller Inventory # 47618295
Quantity: Over 20 available