**1. Introduction**

The main principles of decision-making applied in business practice by advance analytics are summarized in this book [1]. The book is the compilation of chapters written by authors who are experts in the topic covered. Main disciplines, such as management, engineering/technology, economic, etc., are considered as interface with decision-making, being complementary to others, e.g., administrative, finance, risk analysis, marketing, etc.

Decision-making could be defined as the choosing process from several options. It can be done by simple or advanced analytics, by exact or not procedures, by the opinion of any, etc. [2]. The frequency at which the decision-making is done is also variable, from 1 to any. If the effect of decision is considered in a period, then decision-making is classified as operational (short period: daily, weekly, or monthly), strategic (long period: generally 1 year), and politic (very long period: usually more than 1 year).

Decision-making is gaining more importance because the new market scenario is being more competitive [3–6]. This leads the researchers to focus on this topic, together with new technologies and advanced analytics, generating new software and tools based on the Internet of Things [7, 8].

Triantaphyllou analyzed the best decision-making method according to the best decision-making method [9].

The measurement of the efficiency for decision-making units was done via linear and nonlinear programming methods [10]. The authors also took into account the economic and engineering relationship for decision-making.

Hwang and Masud [4] and White [11] showed a complete review of decisionmaking methods. New algorithms are appearing, for example, [12–14], where more robust and complex problems are being solved by employing artificial intelligence [15–17] and the most important ones are presented in this book.

The main theories are studied and presented in this book in different case studies. The main results are analyzed and discussed, suggesting new future works to continue working on that. Case studies are going from simple to complex cases, including big data, from static to dynamic problems, and also from offline to online cases, including the Internet of Things. Models, methods, and algorithms based on dynamic analysis, mathematical optimization, and computational techniques are designed and implemented to carry out the data analysis of decision-making, also considering the constraints.

#### *Advances in Decision Making*

The book has been written to be used by students and professionals of multiple disciplines, e.g., industrial organization, applied microeconomics, business administration, among others, and, of course, decision science applied to simple problems to complex and large problems and for different case studies. The book is also written for academics and researchers on different disciplines.
