Optimal fuzzy hierarchical decisions

Abstract A general multiobjective decision algorithm is developed for evaluating objects in a criteria hierarchy given fuzzy decision input. The Al techniques used are knowledge representation theory (fuzzy sets, logic, and reasoning) and expert systems theory (forward chaining inference). A formal hierarchy theory is developed. Fuzzy theory is reviewed. The fuzzy hierarchical decision (FHD) algorithm is developed from the fuzzy decision work of Bellman, Zadeh, Yager, and Kosko, and stated in full generality. Candidate applications for the FHD algorithm include the salary review problem in a corporate hierarchy of vice-presidents, managers, supervisors, and technical staff. Other managerial and finance applications-as well as cognitive processing hierarchy applications-are under development at VERAC.