Research On The Theory Of Swarm Intelligence Optimization Algorithm And Its Application On Resource Scheduling

Optimization problems exist widely in many fields such as engineering technology, scientific research, economic management and so on. At present, the common optimization algorithm for solving the optimization problems can be divided into classical optimization algorithm, greedy algorithm and local search algorithm, intelligent optimization algorithm, hybrid optimization algorithm and so on. Compare with classical optimization algorithm, intelligent optimization algorithm has a lot of advantages, such as easily operating, fast convergence, good global searching ability, strong robustness and so on. Swarm intelligence optimization is an important branch of intelligence optimization. Individual behaviour and ability of social insect are very simple and limited but colony of social insect can achieve complex tasks in cooperation. Swarm intelligence optimization is inspired from the collective behavior of social insects and is realized by the communication and cooperation between individuals.Artificial Fish Swarm Algorithm (AFSA) is a kind of swarm intelligence optimization algorithm which is proposed by imitating the group behavior of fish. AFSA has many advantages as other swarm intelligence optimization algorithm such as good tolerance of the objective function and parameters setting, fast convergence, good parallelism and so on. As a new swarm intelligence optimization algorithm, AFSA has some shortcomings too, such as convergence slow at the later stage of the optimization process, the low accuracy because of the random factor and so on. In order to improving the performance of AFSA, we proposed twe kinds of Improved Artificial Fish Swarm Algorithm (IAFSA) in this paper:Improved Artificial Fish Swarm Algorithm based on chaotic search and feedback strategy and Quantum Artificial Fish Swarm Algorithm. Multi-modal function optimization problems and multi-objective function optimization problems are two important kinds of function optimization problems. We will research the multi-modal optimization and multi-objective optimization based on AFSA in this paper.Resource scheduling problems is a common optimization problems which we often meet in our real-life situations. It mainly study how to assign finite resources to tasks to optimize some performance criterion under some constraint conditions. Job Shop Scheduling Problem (JSSP) is a very famous resource scheduling problems model and it is also a complicated NP-hard combination optimization problems. Cognitive Radio (CR) is proposed for solving the problem of the scarcity of the radio spectrum and spectrum assignment is one of key technology in CR. Spectrum assignment mainly researches how to assign finite spectrum resources to certain cognitive users to maximize system total benefits and guarantee the fairness of all cognitive users at the same time under the given constraint conditions. Spectrum assignment is a sort of resource scheduling problems. We will research the resource scheduling problems based AFSA and solve the JSSP and spectrum assignment problems using AFSA in this paper.