Mixed-Integer Fractional Programming: Models, Algorithms, and Applications in Process Operations, Energy Systems, and Sustainability

A wide range of optimization problems arising in practical applications can be formulated as mixed-integer fractional programming (MIFP) problems, which combine the combinatorial difficulty of optimizing over discrete variable sets with the challenges of handling the nonconvex fractional objective function. This paper reviews recent developments of tailored global optimization algorithms for large-scale MIFP problems. These MIFP methods are illustrated through three applications: (1) function-unit-based life cycle optimization of sustainable supply chains, (2) integrated optimization of production scheduling and process dynamics of multi-product continuous processes, and (3) optimal design of algae processes for fuel and chemical production.