Intelligent Business Decision-Making in Global Organizations via Fuzzy Reasoning Systems

Abstract

Companies, organizations, governmental departments, and universities need to adopt globalization patterns for their generative survival in dynamic productive outputs. Such outputs are possible only after effective, rational, logical, and systematic treatment of all available input knowledge and information. These inputs mostly have imprecision, uncertainty, vagueness, incompleteness, and missing parts, which together provide a fuzzy arena where an expert is confronted with decision making under a set of conflicting and mutually inclusive vague alternatives. Any uncertain ingredient may be considered as a set of linguistic adjectives attached to the input and output variables so as to refine them into meaningful and less uncertain sub-sets. Logical propositions that combine each sub-set of any input variable to suitable sub-sets of other variables through logical ANDing connectives as precedents are related to a specific sub-set of output as consequent, which constitute fundamental logical rule. These are expert reflections towards management problem solving. The combination of such rules with logical ORing connectives presents linguistically the holistic decision structure of any management system. This chapter presents the essential steps required to achieve decision making under uncertainty for effective management via a fuzzy logic inference system. The basis of fuzzy logic modeling is presented which may be used by different business management experts.