abstract = "Recently, Artificial Intelligence (AI) technology has
been applied to many applications. As an extension of
Genetic Algorithm (GA) and Genetic Programming (GP),
Genetic Network Programming (GNP) has been proposed,
whose gene is constructed by directed graphs. GNP can
perform a global searching, but its evolving speed is
not so high and its optimal solution is hard to obtain
in some cases because of the lack of the exploitation
ability of it. To alleviate this difficulty, we
developed a hybrid algorithm that combines Genetic
Network Programming (GNP) with Ant Colony Optimisation
(ACO). Our goal is to introduce more exploitation
mechanism into GNP. In this paper, we applied the
proposed hybrid algorithm to a complicated real world
problem, that is, Elevator Group Supervisory Control
System (EGSCS). The simulation results showed the
effectiveness of the proposed algorithm.",
notes = "CEC 2007 - A joint meeting of the IEEE, the EPS, and
the IET.