Solving the Model

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ILOG CPLEX generally does not need to be involved while you create your model. However, after the model is set up, it is time to create your cplex object, that is, an instance of the class IloCplex, to be used to solve the model. IloCplex is a class derived from IloAlgorithm. There are other Concert Technology algorithm classes, also derived from IloAlgorithm, as documented in the ILOG CPLEX Reference Manual. Some models might also be solved by using other algorithms, such as the class IloCP for constraint programming, or by using a hybrid algorithm consisting of both ILOG CP or ILOG Solver and ILOG CPLEX. Some models, on the other hand, cannot be solved with ILOG CPLEX.

The makeup of the model determines whether or not ILOG CPLEX can be used to solve it. More precisely, in order to be handled by IloCplex objects, a model may only consist of modeling objects of the classes listed in Table 1.1.

Instances of IloConstraint extracted by ILOG CPLEX can be created in a variety of ways. Most often, they can be generated by means of overloaded C++ operators, such as ==, <=, or >=, in the form expression1 operator expression2. Instances of both IloConstraint and IloRange generated in that way may be built from either linear or quadratic expressions. Constraints and ranges may also include piecewise linear terms. (Other sections of this manual, not specific to C++, show you how to use quadratic expressions: Solving Problems with a Quadratic Objective (QP) and Solving Problems with Quadratic Constraints (QCP). Likewise, Using Piecewise Linear Functions in Optimization: a Transport Example shows you how to apply piecewise linear terms in a C++ application.)

• Extracting a Model
• Invoking a Solver
• Choosing an Optimizer
• Controlling the Optimizers

For an explanation of quadratic constraints, see Solving Problems with Quadratic Constraints (QCP). For more information about quadratic objective functions, see Solving Problems with a Quadratic Objective (QP). For examples of piecewise linear constraints, see Using Piecewise Linear Functions in Optimization: a Transport Example. For more about logical constraints, see Logical Constraints in Optimization. For a description of special ordered sets, see Using Special Ordered Sets (SOS).