A solution (set of values for the decision variables) for which all of the constraints in the Solver model are satisfied is called a feasible solution. An optimal solution is a feasible solution where the objective function reaches its maximum (or minimum) value – for example, the most profit or the least cost.

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## What is feasible solution and optimal solution?

A solution (set of values for the decision variables) for which all of the constraints in the Solver model are satisfied is called a feasible solution. An optimal solution is a feasible solution where the objective function reaches its maximum (or minimum) value – for example, the most profit or the least cost.

## What are the three components of a linear programming problem?

Explanation: Constrained optimization models have three major components: decision variables, objective function, and constraints.

## What are the characteristics of linear programming problems?

Characteristics of Linear Programming Linearity – The relationship between two or more variables in the function must be linear. It means that the degree of the variable is one. Finiteness – There should be finite and infinite input and output numbers.

## What is linear programming problem?

Definition: A linear programming problem consists of a linear function to be maximized or minimized subject to certain constraints in the form of linear equations or inequalities. Set up the following linear programing problems. Do not solve.

## How do you solve a linear programming problem?

Steps to Solve a Linear Programming Problem

- Step 1 – Identify the decision variables.
- Step 2 – Write the objective function.
- Step 3 – Identify Set of Constraints.
- Step 4 – Choose the method for solving the linear programming problem.
- Step 5 – Construct the graph.
- Step 6 – Identify the feasible region.
- Step 7 – Find the optimum point.

## What are the types of linear programming problems?

Linear Programming Problems Terminologies

- Objective Function. It is defined as some numerical value that should be maximized or minimized.
- Constraints.
- Decision Variables.
- Non-negativity Restriction.
- Marketing Management.
- Financial Management.
- Inventory Management.
- Human Resource Management.

## Which of the following is a property of all linear programming problem?

In order for a linear programming problem to have a unique solution, the solution must exist. at the intersection of the nonnegativity constraints. at the intersection of the objective function and a constraint. at the intersection of two or more constraints.

## What is meant by feasible solution of linear programming problem?

Definition: A feasible solution to a linear program is a solution that satisfies all constraints. Definition: An optimal solution to a linear program is the feasible solution with the largest objective function value (for a maximization problem).

## What is an infeasible solution?

Infeasible solution means there is no solution value that will satisfy all the constraints simultaneously.

## What is the importance of linear programming?

Linear programming uses a mathematical or graphical technique to find the optimal way to use limited resources. When you have a problem that involves a variety of resource constraints, linear programming can generate the best possible solution.

## What if there is no feasible region?

Empty Feasible Regions If the feasible region is empty, then there is no maximum or minimum values. An empty region results when there are no points that satisfy all of the constraints. If there are no points that satisfy the constraints, there can be no points to have a maximum or minimum value.

## What is the difference between feasible solution and basic feasible solution?

Degenerate basic feasible solution: A basic feasible solution where one or more of the basic variables is zero. Discrete Variable: A decision variable that can only take integer values. Feasible Solution: A solution that satisfies all the constraints.

## What is degeneracy in linear programming?

Definition: An LP is degenerate if in a basic feasible solution, one of the basic variables takes on a zero value. Degeneracy is a problem in practice, because it makes the simplex algorithm slower.

## How do you know if a solution is feasible?

A feasible solution is one that satisfies all linear and non-linear constraints.

## What is unbounded and infeasible solution?

A linear program is infeasible if its feasibility set is empty; otherwise, it is feasible. A linear program is unbounded if it is feasible but its objective function can be made arbitrarily “good”.

## What is linear programming with example?

Linear programming is used for obtaining the most optimal solution for a problem with given constraints. In linear programming, we formulate our real-life problem into a mathematical model. It involves an objective function, linear inequalities with subject to constraints.

## What is meant by basic feasible solution?

In the theory of linear programming, a basic feasible solution (BFS) is a solution with a minimal set of non-zero variables. Geometrically, each BFS corresponds to a corner of the polyhedron of feasible solutions. If there exists an optimal solution, then there exists an optimal BFS.

## What are the components of linear programming problem?

Constrained optimization models have three major components: decision variables, objective function, and constraints.

## How do you find all basic feasible solutions?

Find all basic feasible solutions & find optimal solution for the given linear programming problem

- First, set x1:=0, then we have x2+x3=3×2−x3=1.
- Next, set x2:=0, then we have −x1+x3=32×1−x3=1.
- Finally, set x3:=0, then we have −x1+x2=32×1+x2=1.

## What is alternative optimal solution in linear programming?

An alternate optimal solution is also called as an alternate optima, which is when a linear / integer programming problem has more than one optimal solution.

## What are the steps of LPP?

Steps to Linear Programming

- Understand the problem.
- Describe the objective.
- Define the decision variables.
- Write the objective function.
- Describe the constraints.
- Write the constraints in terms of the decision variables.
- Add the nonnegativity constraints.
- Write it up pretty.

## What is linear programming problem with example?

Thus, an optimisation problem may involve finding maximum profit, minimum cost, or minimum use of resources etc. A special but a very important class of optimisation problems is linear programming problem. The above stated optimisation problem is an example of linear programming problem.

## What is unbounded solution?

An unbounded solution of a linear programming problem is a situation where objective function is infinite. A linear programming problem is said to have unbounded solution if its solution can be made infinitely large without violating any of its constraints in the problem.