The CSCCP is to search optimal chemical structures, x ∈ Ψ(S), that extend the possible substituents to a configuration of the given scaffold while maximizing the objective function, f(x), such that two constraints, x ∈ Ψ(S) and g(x) ∈ [w min, w max ], are fulfilled.
In Figure 7 we display a second experiment where we generate an initial configuration and an objective configuration of the articulated chain, with the same end-effector.
To test the system, we generate an initial configuration and an objective configuration of the articulated chain.
In the first experiment, displayed in Figure 6, we generate an initial configuration and an objective configuration of the articulated chain, we apply the inverse kinematics approach, with and without image constraint.
Network design models allow to define an optimal network configuration by means of objective functions subject to a series of constraints.
The configuration selection or feature model optimization problem (Benavides et al. 2010) takes a partial configuration of an attributed feature model and an objective function as inputs and returns the full configuration fulfilling the criteria established by the function.
However, the configuration of a proper objective function is not straightforward [ 10].
Consider a couple of objective indicators.
Figures 1 and 2 show the results of 14 different configurations of the objective function.
The latter concerns how to determine an optimal configuration of these identified offerings with the objective of achieving best profit performance.
