铁路公益性客运范围界定混合决策模型

随着国家“基本公共服务均等化”规划的提出和铁路“政企分开”市场化改革的推进,铁路公益性与商业性服务之间的矛盾越发突出. 合理界定铁路公益性客运范围是缓解冲突,实现有效供给的前提. 本文结合定性与定量分析,构建了基于B-C-C三阶段决策流程和 PCFA-FCM降维聚类算法的铁路公益性客运范围界定混合决策模型.B-C-C三阶段决策模型以社会效益、经济状况和现实能力作为层进式判定条件,实现铁路公益性客运范围界定的顶层决策.PCFA-FCM降维聚类算法解决了决策流程实际运作中最难实现的社会效益(公益程度)量化分析问题,可以摆脱列车类型的约束,根据实际指标属性进行分类.

A Compound Decision Model for Defining Scope of Railway Public-welfare Passenger Transportation

With the proposal of "basic public services equalization" plan and the promotion of railway "government-enterprise separation" marketization reform, the contradiction between public welfare and commercial service of railway becomes increasingly prominent. Reasonably defining the scope of public welfare passenger transportation is the precondition to alleviate conflicts and realize effective supply. Combining qualitative and quantitative analysis, this paper constructs a compound decision model for defining the scope of railway public welfare passenger transportation based on B- C-C three- stage decision process and PCFA-FCM dimension- reduced clustering algorithm.The B- C-C three- stage decision model takes social benefits, economic condition and practical capability as the hierarchical judgement conditions to realize the top-level decision-making of the scope of public welfare passenger transport. The PCFA-FCM dimension-reduced clustering algorithm solves the problem of quantitative analysis of social benefits (public welfare degree), which is the most difficult step in the actual operation of decision-making process. It can get rid of the constraint of train type, classify the trains according to the actual index attribute.