ABSTRACT
This chapter reviews the UNIK project, which unifies the Artificial Intelligence (AI) with optimization models for decision support. Our goal is to unify the specification of problems, to encompass as many hybrid types of problems as possible, from both AI and optimization. Currently, the types of problems selected from the AI side are the rules, compatibility constraints, and neural network, while linear programming and integer programming models are selected from the optimization side. A key issue to be resolved for the unification is the unified representation of the optimization model and rules so that they can understand each other. The next issue is designing the unified architecture and devising the solution method. This chapter reviews the above issues one by one, with illustrative applications.
