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Can you give me an example of a linear optimization graph with 2 optimal solutions?
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Can a linear programming problem have multiple optimal solutions?
When solving linear prog. problems, we base our solutions on assumptions.one of these assumptions is that there is only one optimal solution to the problem.so in short NO. BY HADI It is possible to have more than one optimal solution point in a linear programming model. This may occur when the objective function has the same slope as one its binding constraints.
Is it possible for an linear programming model to have exact two optimal solutions?
Yes, but only if the solution must be integral. There is a segment of a straight line joining the two optimal solutions. Since the two solutions are in the feasible region part of that line must lie inside the convex simplex. Therefore any solution on the straight line joining the two optimal solutions would also be an optimal solution.
What is application of linear programming?
It is used in many optimization problems.
Do solutions to systems of linear inequalities need to satisfy linear inequalities?
No. For example, the solution to x ≤ 4 and x ≥ 4 is x = 4.
Can a graph be a function and be linear?
yes as long as the linear graph does have a "y" with infinite solutions and the "x" remains constants for example: x:3,3,3,3,3,3,3 Y:-3,-2,-1,0,1,2,3
Can a linear programming problem have two optimal solutions?
No. However, a special subset of such problems: integer programming, can have two optimal solutions.
Can a linear programming problem have exactly two optimal solutions?
Yes, a linear programming problem can have exactly two optimal solutions. This will be the case as long as only two decision variables are used within the problem.
Can a linear programming problem have multiple optimal solutions?
When solving linear prog. problems, we base our solutions on assumptions.one of these assumptions is that there is only one optimal solution to the problem.so in short NO. BY HADI It is possible to have more than one optimal solution point in a linear programming model. This may occur when the objective function has the same slope as one its binding constraints.
What is optimal solution?
It is usually the answer in linear programming. The objective of linear programming is to find the optimum solution (maximum or minimum) of an objective function under a number of linear constraints. The constraints should generate a feasible region: a region in which all the constraints are satisfied. The optimal feasible solution is a solution that lies in this region and also optimises the obective function.
Is it possible for an linear programming model to have exact two optimal solutions?
Yes, but only if the solution must be integral. There is a segment of a straight line joining the two optimal solutions. Since the two solutions are in the feasible region part of that line must lie inside the convex simplex. Therefore any solution on the straight line joining the two optimal solutions would also be an optimal solution.
What has the author Philip E Gill written?
Philip E. Gill has written: 'Numerical linear algebra and optimization' -- subject(s): Linear Algebras, Mathematical optimization, Numerical calculations 'Practical optimization' -- subject(s): Mathematical optimization
What has the author Shinji Mizuno written?
Shinji Mizuno has written: 'Determination of optimal vertices from feasible solutions in unimodular linear programming' -- subject(s): Accessible book
What has the author Leah W Ratner written?
Leah W. Ratner has written: 'Non-linear theory of elasticity and optimal design' -- subject(s): Elastic analysis (Engineering), Structural design, Structural optimization
What is application of linear programming?
It is used in many optimization problems.
Do solutions to systems of linear inequalities need to satisfy linear inequalities?
No. For example, the solution to x ≤ 4 and x ≥ 4 is x = 4.
What is optimisiom's sturcture?
Optimization is a process of maximizing or minimizing a function by finding its best output. It involves defining a problem, setting objectives and constraints, choosing decision variables, formulating an objective function, and then solving the problem using various optimization techniques like linear programming, gradient descent, or genetic algorithms. The structure of optimization depends on the specific problem being addressed and the approach taken to find the optimal solution.
Can a graph be a function and be linear?
yes as long as the linear graph does have a "y" with infinite solutions and the "x" remains constants for example: x:3,3,3,3,3,3,3 Y:-3,-2,-1,0,1,2,3
