Discover how to locate multiple facilities in convex sets with fuzzy parameters. Our paper presents a linear programming model using block norms, rectilinear, and infinity norms. Optimize the sum of ...

Abstract This paper presents a new heuristic to linearise the convex quadratic programming problem. The usual Karush-Kuhn-Tucker conditions are used but in this case a linear objective function is ...

Efficient linear combination method for multi-objective problems with convex polyhedral preference functions Abstract: At present, the most commonly used method for multiobjective linear programming ...

This letter focuses on the subclass of quadratic programs with linear complementarity constraints. A novel approach to solving a penalty reformulation using sequential convex programming and a ...

Developed and implemented dichotomous, Newton-Raphson, and Gradient Descent algorithms for efficient root-finding in convex functions. Explored the impact of learning rates in Gradient Descent, ...

Learn some techniques for visualizing linear programming solutions using graphs, tables, and software tools. Understand the feasible region, the objective function, and the optimal solution.

An efficient algorithm is proposed for the solution of multiparametric convex nonlinear problems (NLPs). Based on an outer-approximation algorithm, the proposed iterative procedure involves the ...

Solving Semidefinite Programming (SDP) and Linear Matrix Inequalities (LMIs) with YALMIP and MOSEK This code intends to compute the optimal numerical solution to convex constraints in terms of linear ...

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 ...