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Distinguish between integer programming problem and linear programming problem?
Integer programming is a subset of linear programming where the feasible region is reduced to only the integer values that lie within it.
What is the difference between linear and integer programming?
Integer programming is a method of mathematical programming that restricts some or all of the variables to integers. A subset of Integer programming is Linear programming. This is a form of mathematical programming which seeks to find the best outcome in such a way that the requirements are linear relationships.
Can integer linear programming be solved in polynomial time?
No, integer linear programming is NP-hard and cannot be solved in polynomial time.
How do you find the answer to an integer problem?
It depends on the problem: you may have to use integer programming rather than linear programming.
Will the solution to an linear programming problem always consist of integers?
No, it will not. In fact, there is a special branch of linear programming which is called integer programming and which caters for situations where the solution must consist of integers.
What has the author Toshihide Ibaraki written?
Toshihide Ibaraki has written: 'Implicit enumeration algorithm of integer programming on ILLIAC IV' -- subject(s): Computer algorithms, Integer programming 'Adaptive linear classifier by linear programming' -- subject(s): Linear programming 'Arugorizumu to deta kozo (21-seiki o shikoshita denshi tsushin joho karikyuramu shirizu)'
What has the author A N Ahmed written?
A. N. Ahmed has written: 'Experiments in reduction techniques for linear and integer programming' 'A modified production procedure for linear programming problems'
What is NN IN maths?
N squared. It could be the Cartesian plane restricted to integer values, as required for integer linear programming problems.
Can a linear programming problem have two optimal solutions?
No. However, a special subset of such problems: integer programming, can have two optimal solutions.
What is the IP-LP Diff and LP Diff expansion?
The IP-LP Diff (Integer Programming - Linear Programming Difference) refers to the gap between the optimal solutions of an integer programming problem and its linear programming relaxation, where integer constraints are relaxed to continuous ones. LP Diff expansion typically involves analyzing how changes in the coefficients of a linear program can affect the optimal solution, often used to study the robustness of solutions or the sensitivity to perturbations. Both concepts are crucial in understanding the efficiency and performance of optimization algorithms in combinatorial problems.
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 do you understand by linear programming?
1. What do you understand by Linear Programming Problem? What are the requirements of Linear Programming Problem? What are the basic assumptions of Linear Programming Problem?
