MINIMIZATION-PROBLEM-WITH-LINEAR-PROGRAMMING This project explores how to solve a real-world linear programming minimization problem using Python. The objective is to find the optimal production ...

Linear and nonlinear programming are two types of optimization methods that can help you find the best solution to a problem involving decision variables, constraints, and an objective function ...

Abstract: We illustrate some recent results on exact solutions to discrete-time l 1-norm minimization problems with convolution constraints. A fixed-point property for this class of problems is ...

An interior trust-region-based algorithm for linearly constrained minimization problems is proposed and analyzed. This algorithm is similar to trust region algorithms for unconstrained minimization: a ...

Robust linear programming (RLP) is a form of linear programming that aims to find solutions that are feasible and optimal for a range of possible scenarios, rather than a single deterministic ...

Niv Buchbinder, Kamal Jain, Mohit Singh, Secretary Problems via Linear Programming, Mathematics of Operations Research, Vol. 39, No. 1 (February 2014), pp. 190-206 ...

Abstract: A method is described for converting a boolean expression to a disjunctive normal equivalent (two level OR-AND circuit) which is minimal under some criterion presented in advance, as for ...