TY - JOUR
T1 - Study on solution models and methods for the fuzzy assignment problems
AU - Li, Fachao
AU - Xu, Li Da
AU - Jin, Chenxia
AU - Wang, Hong
PY - 2012/9/15
Y1 - 2012/9/15
N2 - In this study, commercing from the structural characteristics of fuzzy information, we propose the concept of level effect function, which can be used to describe fuzziness consciousness and to establish an I L-metric method to measure all aspects of fuzzy information; further, we present an uncertainty metric model of concentrated quantification value; then, we establish two kinds of solution models based on the synthesizing effect of fuzzy assignment problems, by combining the genetic algorithm and assignment problems, and describe a concrete implementation strategy and algorithm to fuzzy assignment problem (denoted by GA⊕SE-FAM, for short); finally, we consider the algorithm's convergence using Markov chain theory, and analyze its performance through simulation of practical examples. All of these indicate that this algorithm possesses the advantages of higher feasibility and easier operationalization, as such, it can be widely used in many fuzzy assignment problems. © 2012 Elsevier Ltd. All rights reserved.
AB - In this study, commercing from the structural characteristics of fuzzy information, we propose the concept of level effect function, which can be used to describe fuzziness consciousness and to establish an I L-metric method to measure all aspects of fuzzy information; further, we present an uncertainty metric model of concentrated quantification value; then, we establish two kinds of solution models based on the synthesizing effect of fuzzy assignment problems, by combining the genetic algorithm and assignment problems, and describe a concrete implementation strategy and algorithm to fuzzy assignment problem (denoted by GA⊕SE-FAM, for short); finally, we consider the algorithm's convergence using Markov chain theory, and analyze its performance through simulation of practical examples. All of these indicate that this algorithm possesses the advantages of higher feasibility and easier operationalization, as such, it can be widely used in many fuzzy assignment problems. © 2012 Elsevier Ltd. All rights reserved.
KW - Fuzzy assignment problem
KW - Genetic algorithm
KW - I L-metric
KW - Level effect function
KW - Markov chain
KW - U L-dispersion
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84861184609&origin=inward
UR - https://www.scopus.com/inward/citedby.uri?partnerID=HzOxMe3b&scp=84861184609&origin=inward
U2 - 10.1016/j.eswa.2012.04.034
DO - 10.1016/j.eswa.2012.04.034
M3 - Article
SN - 0957-4174
VL - 39
SP - 11276
EP - 11283
JO - Expert Systems with Applications
JF - Expert Systems with Applications
IS - 12
ER -