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What is a program that searches for the optimal solution of a problem involving several variables?
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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 does by 'optimal means' mean?
'optimal' means: best possible compromise solution to a problem, when there are several competing considerations, not all of which can be simulataneously maximized.
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 Difference between backtracking and branch and bound method?
Backtracking[1] It is used to find all possible solutions available to the problem.[2] It traverse tree by DFS(Depth First Search).[3] It realizes that it has made a bad choice & undoes the last choice by backing up.[4] It search the state space tree until it found a solution.[5] It involves feasibility function.Branch-and-Bound (BB)[1] It is used to solve optimization problem.[2] It may traverse the tree in any manner, DFS or BFS.[3] It realizes that it already has a better optimal solution that the pre-solution leads to so it abandons that pre-solution.[4] It completely searches the state space tree to get optimal solution.[5] It involves bounding function.
Why are integer programming problems more difficult to solve than linear programming problems?
In both cases the constraints are used to produce an n-dimensional simplex which represents the "feasible region". In the case of linear programming this is the feasible region. But that is not the case for integer programming since only those points within the region for which the variables are integer are feasible.The objective function is then used to find the maximum or minimum - as required. In the case of a linear programming problem, the solution must lie on one of the vertices (or along one line in 2-d, plane in 3-d etc) of the simplex and so is easy to find. In the case of integer programming, the optimal solution so found may contain one or more variables that are not integer and so it is necessary to examine all the points in the immediate neighbourhood and evaluate the objective function at each of these points. This last requirement makes integer programming solutions more difficult to find.
What is the difference between feasible and optimal solution?
The optimal solution is the best feasible solution
State the difference between a feasible solution basic feasible solution and an optimal solution of a lpp?
the optimal solution is best of feasible solution.this is as simple as it seems
Why optimal solution is only at corner point?
feasible region gives a solution but not necessarily optimal . All the values more/better than optimal will lie beyond the feasible .So, there is a good chance that the optimal value will be on a corner point
What is the similar property between dynamic programming and greedy approach?
Both are using Optimal substructure , that is if an optimal solution to the problem contains optimal solutions to the sub-problems
What is the difference between feasible solution and basic feasible solution?
optimal solution is the possible solution that we able to do something and feasible solution is the solution in which we can achieve best way of the solution
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 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.
What does by 'optimal means' mean?
'optimal' means: best possible compromise solution to a problem, when there are several competing considerations, not all of which can be simulataneously maximized.
Why MODX development is the optimal solution for business development?
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Is (-12) a one solution?
A solution is Pareto optimal if there exists no feasible solution for which an improvement in one objective does not lead to a simultaneous degradation in one (or more) of the other objectives. That solution is a nondominated solution.
Does greedy algorithm always work?
Greedy algorithms are only guaranteed to produce locally optimal solutions within a given time frame; they cannot be guaranteed to find globally optimal solutions. However, since the intent is to find a solution that approximates the global solution within a reasonable time frame, in that sense they will always work. If the intent is to find the optimal solution, they will mostly fail.
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.
