中小微企业的多目标信贷决策研究

Research on Multi-Objective Credit Decision-Making for Small and Medium-Sized Enterprises(SMEs)

本文主要研究中小微企业信贷决策问题,将中小微企业相关指标进行量化处理,建立一个多目标优化的信贷决策模型。多目标问题通常对不同目标加权转为单目标的方式处理,这种方法会使得Pareto分布不均匀。为解决这一缺陷,采用NBI方法重新构造信贷决策模型,进一步采用罚函数法对非线性不等式约束及非线性等式约束进行处理,并用改进的粒子群优化算法求解,该算法能显著提高计算效率。最后选取部分中小微企业数据,验证本文模型及算法的有效性,并给出银行信贷决策建议及合理的经济解释。

In order to study the credit decision-making of SMEs,this paper establishes a multi-objective optimization model by quantifying the relevant indicators of SMEs.However,multi-objective problems typically involve weighting different targets into a single target,which can result in uneven Pareto distribution.To address this issue,the NBI method is used to reconstruct the credit decision-making model,the penalty function method is further used to process the nonlinear inequality and nonlinear equality constraints,and solves them with an improved particle swarm optimization algorithm.The algorithm can significantly improve computational efficiency.Finally,data of some SMEs is selected to verify the effectiveness of the model and algorithm,and based on this,suggestions and reasonable explanation for bank credit decision-making are proposed.