COMPLEMENTARITY OF THE GRAPHICAL ANALYSIS FOR INTERACTIVE AID AND DOMINANCE-BASED ROUGH SET APPROACH APPLIED TO THE CLASSIFICATION OF NON-URBAN MUNICIPALITIES

Bryan Boudreau-Trudel, K. Zaras
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Abstract

Graphical analysis for interactive aid (GAIA) and the dominance-based rough set approach (DRSA) are compared as methods of explaining the solution to a multi-criteria ranking problem obtained using the preference ranking organization method for the enrichment of evaluations (PROMETHEE). The classification of 52 municipalities in Northern Quebec in terms of the socioeconomic situation is based on three attributes: home conditions, employment and demographic potential. The classification provided to the decision maker is aggregated information. To facilitate decision-making, the problem is first considered as a sorting task, in which municipalities are distributed into three categories: best (B), worst (W) or intermediate (I), based on the PROMETHEE ranking. In order to improve the position of a municipality thus categorized, the decision maker needs information that will answer the questions: What criteria are relevant to the municipality? What criteria are in conflict? What are the critical values of the criteria? We show that GAIA and DRSA provide convergent and complementary information that allow enrichment of the answers to these questions. Keywords: management decision support, multi-criteria analysis, GAIA, dominance-based rough set approach.
互动式援助图形分析与应用于非城市市镇分类的基于优势的粗糙集方法的互补性
比较了基于优势的粗糙集方法(DRSA)和基于交互式辅助的图形分析方法(GAIA)对基于偏好排序组织方法(PROMETHEE)的多准则排序问题的解法。根据社会经济状况对魁北克北部52个城市进行分类的依据是三个属性:家庭条件、就业和人口潜力。提供给决策者的分类是汇总信息。为了便于决策,这个问题首先被视为一个排序任务,根据PROMETHEE排名,将城市分为三个类别:最佳(B)、最差(W)或中等(I)。为了改善这样分类的市政当局的地位,决策者需要回答以下问题的信息:与市政当局相关的标准是什么?冲突的标准是什么?这些标准的临界值是什么?我们表明,GAIA和DRSA提供了收敛和互补的信息,可以丰富这些问题的答案。关键词:管理决策支持,多准则分析,GAIA,基于优势的粗糙集方法。
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