Quantum Ant Colony Algorithm And Its Application

The 20th century is resplendent age with an all-time development of technogy and civilization. Computers centered Modern Information Processing and digital information characterized Modern Information Transmission is in process of their close combination. As an active research direction of intelligent information processing, computational intelligence (CI) has attracted many scientists' attention. In recent years, CI is generally considered as a new computational method based on the full development of its three branches-Neural Network (NN), Fuzzy System (FS) and Evolutionary Computation (EC). In fact, CI includes abundant implications. Over a long period, the worldwide researchers are going in different directions and using various methods to approach the essence of CI. Naturally, CI is an abstract subject spanning Physics, Mathematics, Computer Science, Communication, Physiology, Evolution and Psychology. Accordingly, using the extracted knowledge of these subjects can make a deeper investigation into CI and give a basis for the optimization, also help to build up a more uniformly intelligence method of system design.In this paper, we introduce the theory of Ant Algorithm and quantum Algorithm firstly, give the model of them, and analyze the characteristic of theirs. Then, we propose a new algorithm, whose cores are those using the quantum algorithm (QA) to optimize the control parameters of the ACS and applying AS to routing. The new algorithm (QACS) is characterized by good global search capability. We use it to solve TSP (Traveling Salesman Problem) and knapsack problem Simulation results show that QACS is superior to conventional heuristic algorithms in quality and efficiency.