Learn what constraints are, how to express them algebraically and graphically, and how to use them to formulate linear programming problems with examples and tips.

Job-shop scheduling is an important but difficult problem arising in low-volume high-variety manufacturing. It is usually solved at the beginning of each shift with strict computational time ...

This paper is devoted to a study of a discrete time infinite horizon optimal control problem with time discounting criterion. We introduce an infinite-dimensional linear programming (IDLP) problem ...

How Linear Programming Software Work LP software incorporates frameworks that are dependent on conventional linear programming algorithms such as simplex and support architecture. These, plus ...

Accordingly, an attempt is made to solve intuitionistic fuzzy linear programming problems using a technique based on an earlier technique proposed by Zimmermann to solve fuzzy linear programming ...

We formulate this problem as a nonlinear Generalized Disjunctive Program (GDP), which, following transformation, results in a large-scale mixed-integer nonlinear programming (MINLP) problem. This ...

Discover the latest research on optimizing solar and wind renewable energy. Explore a new linear formulation for unit commitment problems and efficient solutions using mixed-integer programming. Find ...

In the context of my coursework for the Non-linear Programming course at university, I tackled various non-linear optimization problems using MATLAB. This project serves as a collection of my ...

Mixed-integer linear programming (MILP) is often used for system analysis and optimization as it presents a flexible and powerful method for solving large, complex problems such as the case with ...