Solving problems with quadratic constraints (QCP)
Documents the solution of quadratically constrained programming problems (QCPs), including the special case of second order cone programming problems (SOCPs).
- Identifying a quadratically constrained program (QCP)
Defines the types of quadratically constrained programs that CPLEX solves. - Detecting the problem type of a QCP or SOCP
Documents the criteria that CPLEX components use to detect the problem type of a quadratically constrained program. - Changing problem type in a QCP
Explains considerations about changing the problem type in a quadratically constrained program, according to CPLEX components. - Changing quadratic constraints
Explains special considerations about modifying a constraint containing a quadratic term. - Solving with quadratic constraints
Documents the routine or method to solve a quadratically constrained program. - Numeric difficulties and quadratic constraints
Describes the symptoms of numeric difficulties in a quadratically constrained program. - Accessing dual values and reduced costs of QCP solutions
Outlines a procedure for accessing dual values and reduced costs from QCP solutions. - Accessing dual values and reduced costs of SOCP solutions
Outlines a procedure for accessing dual values and reduced costs from SOCP solutions. - Examples: SOCP
Lists examples of SOCP. - Examples: QCP
Tells where to find sample applications solving a quadratically constrained program.
Parent topic: Continuous optimization