
Learn linear programming and the simplex method to maximize resource utilization and determine the optimum product mix in manufacturing, agriculture, finance, and transport.
Solve a maximization linear programming problem with three variables using Excel solver, applying the simplex method to maximize profit and obtain an objective value of 625.
Learn how to apply the simplex method to maximize profits in a linear program, balancing equations, choosing entering and leaving variables, and interpreting the simplex tableau.
This lecture applies the simplex method to a three-constraint linear program, converting inequalities to equations with slack variables to maximize profit and determine optimal production levels x1 and x2.
Learn how the big-M model modifies the simplex method to convert between minimization and maximization, handling artificial variables and feasible solutions in linear programming.
Master the two-phase method for linear programming by constructing an auxiliary problem, solving the first phase to achieve feasibility, then proceeding to the second phase to optimize the original objective.
Linear Programming refers to those programming models which are used in determining an optimum schedule of interdependent activities in view of the available resources’. They are scientific or mathematical techniques which are used to allocate the limited recourses among the competitive activities so as to optimize the given objective . Linear programming (LP) is a mathematical method for determining a way to achieve the best outcome (such as maximum profit or lowest cost) in a given mathematical model for some list of requirements represented as linear equations. More formally, linear programming is a technique for the optimization of a linear objective function, subject to linear equality and linear inequality constraints. Linear programming can be applied to various fields of study. It is used most extensively in business and economics, but can also be utilized for some engineering problems. Industries that use linear programming models include transportation, energy, telecommunications, and manufacturing. It has proved useful in modeling diverse types of problems in planning, routing, scheduling, assignment, and design.
This course will help in understanding:
Solution of Linear Programming Problem using Simplex Method
Depth Study of Simplex Method and mechanism of solving it effectively
Solution of Maximization case and Minimization case
Solving Linear Programming Problems using Big-M Method and Two Phase Method
Usage of Artificial Variables in Simplex Method
Concept of Non Feasible Solution and Unbounded Solution