The aim of this paper is to introduce a formulation of linear programming problems involving triangular intuitionistic fuzzy numbers for the objecive coefficient. We propose a new method for solving ...

Emily Sharp and Kunal Nabar collaborate on a puzzle that’s greater than the sum of its parts.

We also show a family of linear programs that characterize all algorithms that are allowed to choose J candidates and gain profit from the K best candidates. We believe that a linear programming based ...

This notebook serves as an introduction to Linear Programming and MILP with Python, covering both the concepts and practical applications through various popular optimization problems.

Linear programming provides methods for computing the most practical solutions in production, operations, and supply planning and in the control of complex processes. The introduction of linear ...

Integer linear programming can help find the answer to a variety of real-world problems. Now researchers have found a much faster way to do it.

Bounds and approximate formulae are developed for the average optimum distance of the transportation linear programming (TLP) problem with homogeneously, but randomly distributed points and demands in ...

Karmarkar (1984) found the first method of the interior point algorithm, so linear programming appeared as a dynamic field of research. Soon after, the interior point algorithm was able to resolve ...

This package solves linear and integer programming problems and mixed problems. Bounds can be imposed on the objective function variables. It can even be used to solve systems of linear equations by ...

This study intended to develop a new and improved approach to solve completely Fully Fuzzy Linear Programming Problems(FFLPP) with Symmetric Trapezoidal Fuzzy Numbers(STFN) and findings results are ...