
Learn how to formulate and solve linear programming problems in MATLAB by defining a linear objective, inequality and equality constraints, bounds, and using matrices to encode the model.
Learn to solve a simple linear programming problem in MATLAB with linprog by defining F, A, b, and bounds, negating the objective for maximization, and retrieving x and fval.
Convert the given definitions into a MATLAB script, define the LP problem with A, b, and bounds, solve it, and report the optimum Xopt and its objective value.
Explore solving the transportation problem as a linear programming task in MATLAB, defining the cost matrix, production capacities, and demands, and minimizing total shipping cost under constraints.
Frame a transportation lp in MATLAB using a cost matrix C, flattening to the decision vector and building A and b from production capacities with sub2ind indexing.
Define production capacity and consumer demand constraints in a MATLAB linear programming model, initialize matrices and lower bounds, negate equations, and solve the LP to obtain production and demand results.
Learn how to solve a transportation problem in MATLAB by formulating it as linear programming, building cost, capacity, and demand matrices, and reshaping the solution.
In this video tutorial, the general structure of a Linear Programming (LP) model is reviewed and the general matrix form of LP problems, used by MATLAB, discussed. Then, using linprog function of MATLAB, which is used to deal with linear programming problems, some examples are solved. One of the well-known problems formulated as LP model is the Transportation Problem, which is a simple two-layered supply chain model. In this video tutorial, the general form of Transportation Model is discussed and its solution using MATLAB is implemented step-by-step, with a functional approach.