Premium
A parametric assessment approach to solving facility‐location problems with fuzzy demands
Author(s) -
Lin PeiChun,
Watada Junzo,
Wu Berlin
Publication year - 2014
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.21997
Subject(s) - defuzzification , fuzzy logic , fuzzy number , fuzzy set operations , mathematical optimization , randomness , fuzzy transportation , fuzzy set , computer science , fuzzy classification , mathematics , data mining , operations research , statistics , artificial intelligence
In real‐world applications, sometimes randomness and fuzziness may coexist. In facility‐location problems, the data expressed in natural language may contain vague information. We discuss the uncertainty included in demands in facility‐location problems. The uncertain demand is called fuzzy demand in this paper. In the facility‐location model, the parameters of fuzzy demand are determined by calculating the estimated expected value of the fuzzy demand, which is obtained by using the estimated parameters of the underlying probability distribution function of the fuzzy data. Moreover, we propose a defuzzification formula of the fuzzy demand called the realization of fuzzy demand . The defuzzification formula of fuzzy demand comprises the upper bound and the lower bound of the fuzzy demand. Moreover, the error of the fuzzy demand is assessed as the mean absolute percentage error of the fuzzy demand. Empirical studies show that we can solve real‐life location problems by using the defuzzification formula of fuzzy demand and get higher profit in our facility‐location model than by using conventional methods. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.