Optimization — that is, finding the minima and maxima of real-valued functions — is one of the most important problems throughout science and engineering. Minimization principles naturally arise in the fitting of data and in machine learning, where one seeks to minimize an appropriately chosen “loss function”. The equilibrium solutions of systems of physical significance seek to minimize their potential energy. Engineering design is guided by a variety of optimization constraints, such as performance, longevity, safety, and cost. Additional applications naturally appear in economics and financial mathematics — one often wishes to minimize expenses or maximize profits — in biological and ecological systems, in pattern recognition and signal processing, in statistics, and many other fields.