Name | Description | Type | Package | Framework |
FerrisMangasarianWrightPhase1 | The phase 1 procedure finds a feasible table from an infeasible one by pivoting the simplex table of a related problem. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex | SuanShu |
FerrisMangasarianWrightPhase2 | This implementation solves a canonical linear programming problem that does not need preprocessing its simplex table. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solver | SuanShu |
FerrisMangasarianWrightScheme2 | The scheme 2 procedure removes equalities and free variables. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex | SuanShu |
JordanExchange | Jordan Exchange swaps the r-th entering variable (row) with the s-th leaving variable (column) in a matrix A. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex | SuanShu |
LPBoundedMinimizer | This is the solution to a bounded linear programming problem. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solution | SuanShu |
LPCanonicalProblem1 | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.problem | SuanShu | |
LPCanonicalProblem2 | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.problem | SuanShu | |
LPCanonicalSolver | This is an LP solver that solves a canonical LP problem in the following form. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solver | SuanShu |
LPDimensionNotMatched | This is the exception thrown when the dimensions of the objective function and constraints of a linear programming problem are inconsistent. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.exception | SuanShu |
LPEmptyCostVector | This is the exception thrown when there is no objective function in a linear programming problem. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.exception | SuanShu |
LPException | This is the exception thrown when there is any problem when solving a linear programming problem. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.exception | SuanShu |
LPInfeasible | This is the exception thrown when the LP problem is infeasible, i. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.exception | SuanShu |
LPMinimizer | An LP minimizer minimizes the objective of an LP problem, satisfying all the constraints. | Interface | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp | SuanShu |
LPNoConstraint | This is the exception thrown when there is no linear constraint found for the LP problem. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.exception | SuanShu |
LPProblem | A linear programming (LP) problem minimizes a linear objective function subject to a collection of linear constraints. | Interface | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.problem | SuanShu |
LPProblemImpl1 | This is an implementation of a linear programming problem, LPProblem. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.problem | SuanShu |
LPRuntimeException | This is the exception thrown when there is any problem when constructing a linear programming problem. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.exception | SuanShu |
LPSimplexMinimizer | A simplex LP minimizer can be read off from the solution simplex table. | Interface | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solution | SuanShu |
LPSimplexSolution | The solution to a linear programming problem using a simplex method contains an LPSimplexMinimizer. | Interface | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solution | SuanShu |
LPSimplexSolver | A simplex solver works toward an LP solution by sequentially applying Jordan exchange to a simplex table. | Interface | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solver | SuanShu |
LPSolution | A solution to an LP problem contains all information about solving an LP problem such as whether the problem has a solution (bounded), how many minimizers it has, and the minimum. | Interface | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp | SuanShu |
LPSolver | An LP solver solves a Linear Programming (LP) problem. | Interface | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp | SuanShu |
LPStandardProblem | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.problem | SuanShu | |
LPTwoPhaseSolver | This implementation solves a linear programming problem, LPProblem, using a two-step approach. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solver | SuanShu |
LPUnbounded | This is the exception thrown when the LP problem is unbounded. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.exception | SuanShu |
LPUnboundedMinimizer | This is the solution to an unbounded linear programming problem. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solution | SuanShu |
LPUnboundedMinimizerScheme2 | This is the solution to an unbounded linear programming problem found in scheme 2. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solution | SuanShu |
NaiveRule | This pivoting rule chooses the column with the most negative reduced cost. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.pivoting | SuanShu |
SimplexPivoting | A simplex pivoting finds a row and column to exchange to reduce the cost function. | Interface | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.pivoting | SuanShu |
SimplexPivoting .Pivot | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.pivoting | SuanShu | |
SimplexTable | This is a simplex table used to solve a linear programming problem using a simplex method. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex | SuanShu |
SimplexTable .Label | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex | SuanShu | |
SimplexTable .LabelType | the artificial variable, x0, pp. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex | SuanShu |
SmallestSubscriptRule | Bland's smallest-subscript rule is for anti-cycling in choosing a pivot. | Class | com.numericalmethod.suanshu.optimization.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.pivoting | SuanShu |