Intelligent Multi-objective Optimization Applied Research In The Fire Distribution

There are many problems of fire distribution in modern high-tech war, which can often be abstracted to multi-objective optimization problems. The improved non-dominated sorting genetic algorithm (NSGA-Ⅱ) is proposed in the paper, which is used to solve the fire distribution problem with two objective functions successfully. The primary work of this paper includes:1) The general process and the fundamental theory of genetic algorithm is introduced systematically, which is also be applied to an example;2) The penalty function method and the constraint toumament method are introduced in the paper, which are used to process the constraint limit. Via analyzing the basic principle of NSGA-Ⅱ, which is elaborated in the paper, the fast nondominated sorting method, congestion distance and its comparison operator, the elite strategy and the main process of NSGA-Ⅱis researched particularly.3) Via modeling the fire distribution problem, the model is computed by the algorithm of NSGA-Ⅱ, which is combined with both the penalty function method and the restraint league tournament method The optimization of two goals are also realized in the paper.The results derived from the VC++6.0 indicate that, two algorithms both have the high convergence, simultaneously the Pareto optimal solution also maintain the variety of distribution.