Application of rough sets for environmental decision support in industry

Abstract

Practical environmental decision-making in industry is a complex task that often entails a subtle interplay between alternatives and criteria. Quantitative tools are used to aid decision-makers to arrive at rational conclusions. However, conventional decision aids are often limited by the need to define a priori weights for the criteria being considered; identifying the correct weights to use is not a trivial task and has been the subject of considerable research. An alternative approach based on rough set methodology is described in this work. The procedure develops an empirical, rule-based model from example responses derived from an expert panel. The model can then be used for decision-making in cases resembling the example used previously. Rough set theory also provides numerical measures of the reliability of the rule-based model developed. The approach is illustrated with two case studies, the first involving comparison of alternative energy sources, and the second involving the ranking of pollution prevention strategies in manufacturing.