Eugene J. Zak – författare

Written by an experienced operations research practitioner with a strong applied mathematics background, this book offers practical insights into how to approach optimization problems, how to develop intelligent and efficient mathematical models and algorithms, and how to implement and deliver software products to customers. With a focus on revealing the similarities and differences between academia and industry in mathematical modeling, the book provides useful tips and advice based on the author’s extensive experience as a principal developer working to solve real-world optimization problems for several major high-tech companies.The book offers valuable food for thought for researchers and practical guidance for graduate students preparing for their future projects in the industry. It is also an essential resource for practitioners working in the industrial, business, and service sectors.“The book’s presentation style is very enjoyable, and Zak keeps the focus on the practical aspects of the problems as they occur in the industry. Though practitioners are the primary target audience, students and academics can also benefit from the book as are reference to the current state of the art.” (Paparao Kavalipati, Computing Reviews, January 3, 2025)

This book uniquely explores popular optimization, presenting fundamental problems from diverse sources. It aims to cultivate a non-traditional problem-solving approach applicable to both optimization and broader contexts. The author introduces optimization models for well-known problems and proposes several new ones. Additionally, familiar problems from various fields are reformulated into optimization frameworks.The book serves as a curated collection of intriguing problems, most of which have clear practical applications. For each problem, multiple solution techniques are provided, typically offering at least two distinct approaches. It also demonstrates how AI can assist readers in formulating and formalizing problems that require robust mathematical models. AI’s benefits are highlighted throughout the decision-making process, from fine-tuning input data to effectively presenting results. The selected optimization problems span both continuous and discrete domains, including linear and nonlinear formulations.The richness and depth of the content will be appreciated by both students and practitioners as they explore the variety of methods that can be applied to solve more complex, real-world problems.