Draw in the vector representing the gradient of the objective function. Graph the feasible region by plotting the line associated with each of the linear inequality constraints.They are typically associated with “natural” or “common sense” restrictions on the decision variable. Implicit constraints are not explicitly given in the problem statement. Explicit constraints are those that are explicitly given in the problem statement. Determine the explicit constraints and write a functional expression for each of them.

Read more: Excel Solver with a Case Study Maximize profit where profit = 8A + 11B+9C

Determine the objective and use the decision variable to write an expression for the objective function.

Number of joysticks to be produced each month Number of keyboards to be produced each month In our example, we need to determine how many mice, keyboards, and joysticks are to be produced each month.

Identify and label the decision variable.

To solve the above problem, we need to develop an LP model by following steps: Linear Programming (LP) is a technique for the optimization of a linear objective function while subject to linear equality or linear inequality constraints. How to solve above problem using Linear Programming How can the manufacturer maximize its monthly profit contribution from the plant? 2. The per-unit profit, per-unit labor usage, monthly demand, and per-unit machine time usage are given in the following table.Įach month, a total of 13,000 labor hours and 3,000 hours of machine time are available.

Suppose that a computer manufacturing plant produces mice, keyboards, and video game joysticks. The problem to be solved in this articleīefore introducing what is LP, let’s take a look at the problem we are going to solve today.

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