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The space of all candidate solutions, before any feasible points have been excluded, is called the feasible region, feasible set, search space, or solution space. [2] This is the set of all possible solutions that satisfy the problem's constraints. Constraint satisfaction is the process of finding a point in the feasible set.
An interior point method was discovered by Soviet mathematician I. I. Dikin in 1967. [1] The method was reinvented in the U.S. in the mid-1980s. In 1984, Narendra Karmarkar developed a method for linear programming called Karmarkar's algorithm, [2] which runs in provably polynomial time (() operations on L-bit numbers, where n is the number of variables and constants), and is also very ...
A closed feasible region of a problem with three variables is a convex polyhedron. The surfaces giving a fixed value of the objective function are planes (not shown). The linear programming problem is to find a point on the polyhedron that is on the plane with the highest possible value.
The possible results of Phase I are either that a basic feasible solution is found or that the feasible region is empty. In the latter case the linear program is called infeasible. In the second step, Phase II, the simplex algorithm is applied using the basic feasible solution found in Phase I as a starting point.
The blue region is the feasible region. The tangency of the line with the feasible region represents the solution. The line is the best achievable contour line (locus with a given value of the objective function).
A barrier function is also called an interior penalty function, as it is a penalty function that forces the solution to remain within the interior of the feasible region. The two most common types of barrier functions are inverse barrier functions and logarithmic barrier functions.
Download as PDF; Printable version; ... Feasible region, a region that satisfies mathematical constraints;
The affine scaling method is an interior point method, meaning that it forms a trajectory of points strictly inside the feasible region of a linear program (as opposed to the simplex algorithm, which walks the corners of the feasible region). In mathematical optimization, affine scaling is an algorithm for solving linear programming problems.