Researchers utilise models that blend bilevel optimisation, mixed-integer nonlinear programming (MINLP) and distributed algorithms such as the alternating direction method of multipliers (ADMM) to ...

In addition, two algorithms are presented for approximately solving fractional programming (FP) problems. The first algorithm is based on an objective space cut and bound method for solving convex FP ...

MG4C6.2 Mathematical Programming: Introduction to theory and the solution of linear and nonlinear programming problems: basic solutions and the simplex method, convex programming and KKT conditions, ...

This paper presents a realistic chemical-process optimization problem in detail, and notes the fact of its equivalence to the general nonlinear programming problem. The eight equality constraints that ...

Lookup tables and Taylor series are two common methods for interpolating between experimentally gathered data or for generating a known function such as a ...

This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving algorithmic problems that seek optimal ...