Double-Deck Elevator System Uing Genetic Network Programming with Genetic Operators Based on Pheromone Information

Genetic network programming (GNP), one of the extended evolutionary algorithms was proposed, whose gene is constructed by the directed graph. GNP can perform a global searching, but it lacks of the exploitation ability. Since the behavior of GNP is characterized by the balance between exploitation and exploration in the search space, we proposed a hybrid algorithm in this paper that combines GNP with ant colony optimization (ACO). The genetic operators are operated using the pheromone information in some special generations. 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.