View on Coursera Course Description This course continues our data structures and algorithms specialization by focussing on the use of linear and integer programming formulations for solving ...

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 ...

Subway timetabling problems are important but difficult discrete optimization problems that are usually solved with strict computational time requirements in order to minimize passenger waiting time ...

It provides implementations for various algorithms for solving discrete optimal transport problems, via the linear programming formulation due to Kantorovich. It includes a naive dense solver for ...

Linear Programming Model Formulation: In this section, I constructed a linear programming model to determine the most cost-effective weekly diet that satisfies my nutritional requirements. The ...

A zero-one (0-1) linear programming formulation of multiproject and job-shop scheduling problems is presented that is more general and computationally tractable than other known formulations. It can ...

This paper proposes a mixed integer linear programming (MILP) formulation for robust state estimation (RSE). By using the exactly linearized measurement equations instead of the original nonlinear ...

William H. Evers, A New Model for Stochastic Linear Programming, Management Science, Vol. 13, No. 9, Series A, Sciences (May, 1967), pp. 680-693. Free online reading for over 10 million articles; ...