In this paper, we amend a multi-criteria methodology known as MURAME, to evaluate the creditworthiness of a large sample of Italian Small and Medium-sized Enterprises, using as input their balance sheet data. This methodology produces results in terms of scoring and of classification into homogeneous rating classes. A distinctive goal of this paper is to consider a preference disaggregation method to endogenously determine some parameters of MURAME, by solving a nonsmooth constrained optimization problem. Because of the complexity of the involved mathematical programming problem, for its solution we use an evolutionary metaheuristic, coupled with a specific efficient initialization. This is combined with an unconstrained reformulation of the problem, which provides a reasonable compromise between the quality of the solution and the computational burden. An extensive numerical experience is reported, comparing an exogenous choice of MURAME parameters with our approach.

在本文中，我们修订了一种称为MURAME的多准则方法，以使用其资产负债表数据作为输入来评估大量意大利中小企业样本的信誉度。这种方法产生的结果包括评分和分类到同类评分类别中。本文的一个独特目标是考虑内在偏好分解方法通过解决非平滑约束优化问题来确定MURAME的某些参数。由于所涉及的数学编程问题的复杂性，对于其解决方案，我们使用进化的元启发式方法以及特定的有效初始化方法。这与问题的不受约束的重新组合结合在一起，从而在解决方案的质量和计算负担之间提供了合理的折衷。报告了丰富的数值经验，将外来选择的MURAME参数与我们的方法进行了比较。