Second, the conversion to a single-objective optimization problem involves additional constraints. Third, since most real-world goal programming problems involve nonlinear criterion functions, the ...

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, ...

Nonlinear Programming algorithms cannot consistently find global minima. All the algorithms in PROC NLP find a local minimum for this problem. If you need to check whether the obtained solution is 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 ...