The Simulated Annealing Algorithm And Its Application

It is an obstacle to human being developing because of went short of energy sources increasingly. In order to solve energy sources dangerous and develop harmoniously between human being and nature, saving energy sources has become a mainstream in the world today.For years, our country has been in the lack of electricity energy. Though it is affluent in water, the Yunnan province has been lack of electricity energy. Especially new charge rule was established, for corporation depending on electricity energy, that is bad thing. For reducing the electricity expenditure, the thesis was put forward to solve the problem.In the case of lacking electricity the corporation still adopt constant current to Electrolytic Deposition Process of Zinc, that will rise expenditure and be disadvantage of market competition. Taking care of introducing variable current, it is a problem that is searching current' s optimization combination.In order to solve this problem this paper study and use the simulated annealing algorithm(SA). SA is a new random grabble. It was put forward to solve large dimension combinatorial problem. It is an efficient approximate method. Comparing with other algorithms, SA has advantage of simple description, flexible using, high efficient and so on. SA make up of state producing function, acceptance function and temperature updating function, and outer and inner rules. Designing theses factors will influence SA' s velocity, convergence and robust. In chapter 2, introduce the classic simulated annealing, including algorithm structure, mathematical model and actualizing in the fixed time. In chapter 3, discuss the disadvantage of SA and put forward improved aspect. In chapter 4, using linear programming establish the output dividing model and the objective function' s value being minimum' s model. And using SA searchthe optimizationaJ combination of current.The process and fundament of simple SA are introduced. The basic of physics are presented firstly. In the base of Electrolytic Depositior Process of Zinc, using linear programming knowledge and optimizatior theory, establishing output distribution mathematical model anc multi-goal' s day current density mathematical model, using improved Sh searching optimization combination, and reducing cost.