Formulating a linear programming problem requires identifying the decision variables, the objective function, and the constraints that apply to the problem.

Learn how to identify and resolve infeasibility in linear programming problems using common methods and tools. ... or using a different mathematical formulation or technique can be useful.

We introduce a novel linear programming approach to the maximum lifetime routing problem. To the best of our knowledge, this is the first mathematical programming of the maximum lifetime routing ...

Explore our innovative technique for solving intuitionistic fuzzy linear programming problems without the need for existing rankings ... The advantage of the IFO problem is two-fold: they give a rich ...

A Mixed-Integer-Linear-Programming (MILP) problem, formulation, and solution for a power systems generator biding strategy. The objective function is the sum of the unit price of the MW multiplied by ...

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 large-scale problem is intractable using traditional MINLP approaches. By using ML surrogates to predict required system costs and performance indicators, we can approximate the nonlinearities in ...

Fuzzy linear programming problem with fuzzy coefficients was formulated by Negoita [7] and are called robust programming. Dubois and Prade investigated optimization with linear fuzzy constraints [8] .