1. This dissertation defines the heuristic information in ACO properly and designs the corresponding ACO's state transition rule and pheromone updating rule.

2. We genetic transformation of ACO antisense gene into lily's bulb and leafstalk by Agrobacterium tumefaciens - mediated method.

3. Ant Colony Optimization (ACO) is a new-style simulating evolution algorithm. The behavior of real ant colonies foraging for food is simulated and used for solving optimization problems.

4. After the algorithm being proposed, ACO has applied into TSP, quadratic assignment, graph coloring, vehicle route successfully.

5. In this paper, ACO algorithm is reviewed by and large. Firstly, the corresponding principle of biont and the implementing framework for ACO algorithm are introduced simply.

6. Realize DN - ACO target tracking algorithm in simulation platform and verify the energy efficiency of the algorithm.

7. After lots of experiments ACO has exhibited its excellent performance and efficiency in experiments for solving a great lot of combinatorial optimization problems, and now it is used in many areas.

8. ACO is used to solve combination optimization ( CO ) problems and gets a good effect.

9. The applications of ACO to static and dynamic COPs, such as traveling salesman problem, quadratic assignment problem[http://], network routing problem are reviewed.

10. Ant Colony Optimization (ACO), which is introduced in this paper because of the ability of resisting combination explosion to NP-hard problem, now is used to solve the problem of DNO.

11. An improved ant colony optimization ( ACO ) algorithm is utilized in cell scheduling of flexibleforinstrumentand time.

12. During the ACO system emulation experiment, many uncertain factors of pheromone updating are found.

13. The system combined the Ant Colony Optimization (ACO) algorithm and the dispatching priority heuristic algorithm to solve the scheduling problems existing in mold parts with work piece restrictions.

14. Owing to its positive feedback and effective parallelization and strong lustiness , ACO has been applied in many fields.

15. A hybrid algorithm for unit commitment problem optimization ( ACO ) and particle swarm optimization ( PSO ) is proposed.

16. Acetoin was shown to function as an inducer for the expression of aco genes, whereas glucose exhibited a repression effect.