A new class of intelligent knowledge-based systems with an optimisation-based inference engine

摘要

In this paper we describe a new class of intelligent knowledge-based system (IKBS) which can be used principally for managerial decision making applications. This class of applications often requires a framework for knowledge acquisition which allows the system to use the knowledge of several experts. In addition, since in most business decision making the objective is maximise profits, there is a need for an inference engine which allows optimisation to be carried out. The new class of IKBS which is described in this paper has both these properties, i.e., the ability to use the knowledge of multiple experts in a convenient way and an inference engine which by performing optimisations is able to pick out the profit maximising decisions. As an illustration of these concepts, a system for allocation decision making is described. The system ‘Retail-opt’ allows the user to solve problems like allocation of space in retail outlets, allocation of space in mail order catalogues, pricing policy decisions for discounted airline tickets, etc. In the paper, the basic concepts behind ‘Retail-opt’ are described and an application of ‘Retail-opt’ to the problem of retail space allocation in a Scandinavian Department Store is given. A number of other systems which use these concepts for more complicated competitive decision making situations are also described.