![]() Frequently, the decision-making process is guided by experience. The manager also faces complex decisions-decisions which, as a rule, involve several people and many variables, for which various criteria need to be into account to solve them, some of which may not be quantifiable but are important, or may be important at a later time. It is this complexity that necessitates an extended evaluation phase in decision problems. Decision-making problems are of different sorts, presenting different challenges there may be more than one solution to a problem, or a number of criteria in relation to which the alternative solutions have to be evaluated, or a number of alternative possible future scenarios in which different solutions would be optimal. This complicates a manager’s decision making, especially when the decisions are critical for the future of the business. Practically, decision making has an impact on a variety of factors that in some cases come into conflict with each other. The paper’s findings offer an important guide for managers to improve decision making and enhance performance in competitive markets. Through a case study, this paper explores the AHP, a method with three levels in which the identification of decision-making criteria is based on the perceptions of managers and consumers. We would like to show that the AHP method could be of great use in decision making. One of these is the Analytic Hierarchy Process (AHP) method-a method which should receive more attention than it has up to now. Various methods have been developed for multi-criteria decision making. In order to find appropriate methods for assessing and prioritizing goals, new approaches to decision making should be adopted. Currently, in the countries in the Albanian-speaking regions of the Western Balkans, intuitive decision-making methods predominate. Managers are therefore interested in acquiring and implementing reliable methods for making decisions both now and in the future. A reverse-flow technique is described for the solution of a functional equation arising in connection with a decision process in which the termination time is defined implicitly by the condition that the process stops when the system under control enters a specified set of states in its state space.Decision making is a significant responsibility for business managers, their decisions impacting business performance. By using dynamic programming, the determination of a maximizing decision is reduced to the solution of a system of functional equations. The use of these concepts is illustrated by examples involving multistage decision processes in which the system under control is either deterministic or stochastic. A maximizing decision is defined as a point in the space of alternatives at which the membership function of a fuzzy decision attains its maximum value. ![]() A fuzzy decision, then, may be viewed as an intersection of the given goals and constraints. The italicized words are the sources of fuzziness in these examples.įuzzy goals and fuzzy constraints can be defined precisely as fuzzy sets in the space of alternatives. Similarly, an example of a fuzzy goal is: “ x should be in the vicinity of x 0 ,” where x 0 is a constant. This means that the goals and/or the constraints constitute classes of alternatives whose boundaries are not sharply defined.Īn example of a fuzzy constraint is: “The cost of A should not be substantially higher than α,” where α is a specified constant. By decision-making in a fuzzy environment is meant a decision process in which the goals and/or the constraints, but not necessarily the system under control, are fuzzy in nature.
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