XSLP_REFORMULATE

Controls the problem reformulations carried out before augmentation. This allows SLP to take advantage of dedicated algorithms for special problem classes.

Integer

Bit	Meaning
0	Solve convex quadratic objectives using the XPRS library .
1	Convert non-convex quadratic objectives to SLP constructs .
2	Solve convex quadratic constraints using the XPRS library.
3	Convert non-convex QCQP constraints to SLP constructs.
4	Convexity of a quadratic only problem may be checked by calling the optimizer to solve the instance.
5	Convert pievewise linear functions to MIP constructs.
6	Convert ABS functions to MIP constraints if the full problem can be made not nonlienar.
7	Convert MIN and MAX functions to MIP expressions if the full problem can be made not nonlinear.
8	Always convert ABS expressions.
9	Always convert MIN and MAX expressions.

-1: All structures are checked against reformulation

The reformulation is part of XSLP presolve, and is only carried out if XSLP_PRESOLVE is nonzero.

The following constants are provided for setting these bits:

Setting bit 0	XSLP_REFORMULATE_SLP2QP
Setting bit 1	XSLP_REFORMULATE_QP2SLP
Setting bit 2	XSLP_REFORMULATE_SLP2QCQP
Setting bit 3	XSLP_REFORMULATE_QCQP2SLP
Setting bit 4	XSLP_REFORMULATE_QPSOLVE
Setting bit 5	XSLP_REFORMULATE_PWL
Setting bit 6	XSLP_REFORMULATE_ABS
Setting bit 7	XSLP_REFORMULATE_MINMAX
Setting bit 8	XSLP_REFORMULATE_ALLABS
Setting bit 9	XSLP_REFORMULATE_ALLMINMAX

XSLPconstruct, XSLPminim, XSLPmaxim, XSLPreminim, XSLPremaxim, XSLPnlpoptimize, XSLPglobal