This book presents a self-contained introduction to quantum algorithms, with a focus on quantum optimization—quantum approaches to solving optimization problems. It equips readers with the essential tools to assess the strengths and limitations of these algorithms, emphasizing provable guarantees and computational complexity. The first comprehensive treatment of quantum optimization, Quantum Algorithms for Optimizers provides a rigorous introduction to the computational model of quantum computers and to the theory of quantum algorithms, contains detailed discussions of some of the most important developments in quantum optimization algorithms, and summarizes the most significant advances in the open literature. Giacomo Nannicini is an associate professor in the Daniel J. Epstein Department of Industrial and Systems Engineering, with a courtesy appointment in the Ming Hsieh Department of Electrical and Computer Engineering, at the University of Southern California. He is the recipient of the 2021 Beale–Orchard-Hays Prize, the 2016 COIN-OR Cup, the 2015 Robert Faure Prize, and the 2012 Glover-Klingman Prize. His main research and teaching interests are optimization and its applications.