基于遗传算法的装备采购决策优化研究

在装备采购中，由于需求单位地域分布和担负的任务各不相同，对装备的品种、数量、时限要求也就不一样，如何使装备采购科学化、合理化，是一个涉及多变量、多目标的复杂系统问题。在综合考虑装备采购各项因素的基础上，构建多约束条件下的多目标模糊指派模型，提出了基于遗传算法的解决方案，最后通过案例进行仿真实验，验证该算法的可行性和有效性，解决了采用传统优化方法难以解决的装备采购优化决策问题。

Equipment Procurement Optimization Based on Genetic Algorithm

Equipment procurement constitutes an important aspect of equipment development, and it is the last link in the whole generation process of equipment from putting forward demand to forming combat capability. The success or failure of this work directly affects the quality of military equipment and the generation of combat effectiveness. At present, empirical decision making, which depends on the experience, knowledge and preferences of decision makers, can no longer meet the demands of equipment purchasing decisions. Therefore, it is urgent to explore and build a reasonable model in accordance with the characteristics of purchasing decisions, making full use of the intelligent optimization algorithm to solve the problems in realizing the optimal decision-making of equipment procurement. On the basis of synthetically considering the various factors of equipment procurement, the approach is put forward to transform the equipment procurement problem into a multi-objective fuzzy assignment problem under multi-constraint conditions, and a solution based on genetic algorithm is given. Finally, a case study is carried out to verify the feasibility and effectiveness of the algorithm. At the same time, the efficiency of the genetic algorithm and the Hungarian algorithm is compared. The experimental results show that the efficiency of genetic algorithm is much better than that of Hungarian algorithm, and with the increase of the scale of the problem, the difference of solving time is even more obvious. The complex problem of equipment purchasing decision optimization is solved, which is difficult to achieve by the traditional optimization method, and it has good application effect in practical situations, so it has significant practical value for equipment purchasing decision making. At the same time, the model put forward in this paper also has some reference value for constructing and solving other assignment problems.