Ads
related to: linear programming problems examples- Pricing
Get a better price on our services
Choose your discipline & task size
- Java
Getting Help with Java is Easy
Team of Java Experts is Here
- R Programming
R Programming Assignment Help
Fast, Accurate & Reliable Help
- WOW Support - 24/7
Reach us whenever you need
Chat, Phone, Email
- JavaScript
Advanced JavaScript Assignment Help
High-Quality Help with JavaScript
- Php
Dependable Php Assignment Help
Get Instant Help with Php Task
- Pricing
Search results
Results From The WOW.Com Content Network
However, some problems have distinct optimal solutions; for example, the problem of finding a feasible solution to a system of linear inequalities is a linear programming problem in which the objective function is the zero function (i.e., the constant function taking the value zero everywhere).
Generalized assignment problem; Integer programming. The variant where variables are required to be 0 or 1, called zero-one linear programming, and several other variants are also NP-complete [2] [3]: MP1 Some problems related to Job-shop scheduling; Knapsack problem, quadratic knapsack problem, and several variants [2] [3]: MP9
In large linear-programming problems A is typically a sparse matrix and, when the resulting sparsity of B is exploited when maintaining its invertible representation, the revised simplex algorithm is much more efficient than the standard simplex method. Commercial simplex solvers are based on the revised simplex algorithm.
An example is the simplex algorithm in linear programming, which works surprisingly well in practice; despite having exponential worst-case time complexity, it runs on par with the best known polynomial-time algorithms. [4]
There is a close connection between linear programming problems, eigenequations, and von Neumann's general equilibrium model. The solution to a linear programming problem can be regarded as a generalized eigenvector. The eigenequations of a square matrix are as follows:
A problem with five linear constraints (in blue, including the non-negativity constraints). In the absence of integer constraints the feasible set is the entire region bounded by blue, but with integer constraints it is the set of red dots. A closed feasible region of a linear programming problem with three variables is a convex polyhedron.