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Fuzzy stochastic dynamic programming for marketing decision support
Author(s) -
Weber Klaus,
Sun Zhaohao
Publication year - 2000
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
DOI - 10.1002/1098-111x(200008)15:8<763::aid-int5>3.0.co;2-w
Subject(s) - computer science , dynamic programming , stochastic programming , profit (economics) , fuzzy logic , set (abstract data type) , mathematical optimization , fuzzy set , process (computing) , operations research , artificial intelligence , mathematics , algorithm , economics , programming language , microeconomics , operating system
One of the most important goals in marketing is to realize the highest profit by applying appropriate means to optimize the process of acquiring customers. To assist the marketer in making marketing decisions, this paper introduces a stochastic dynamic programming model for the process of acquiring customers. It is actually a stochastic multistage decision process, whose state space consists of granularized information on customers and whose transitions are controlled by marketing actions. Then it shows how to control this process using fuzzy constraints and how to characterize the goal of maximizing profit by a fuzzy set. After an overview of approaches in dynamic programming under fuzziness given by Bellman and Zadeh, this paper further presents a new model of fuzzy stochastic dynamic programming to solve the decision problem for a stochastic system with implicitly defined termination time. It is argued that this study can facilitate research and development of both financial engineering and e‐commerce. © 2000 John Wiley & Sons, Inc.