An adaptive decision aid for real environments

Decision making in the real world is concerned with both deterministic models and undeterministic human expertise. However. Both current decision-making methods use either mathematical programming or heuristic rules; each approach by itself loses the other piece of information. This paper proposes a new approach to integrate these two different types of information simultaneously and adaptively. It uses fuzzy mathematical programming to quantitatively model objectives and resource constraints, and a linguistic knowledge base to qualitatively model imprecise human expertise. The coordination between these two modules and the new idea of subjective knowledge adaptation for human-in-the-loop systems are discussed in detail