Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 11276-11283 |
| Number of pages | 8 |
| Journal | Expert Systems with Applications |
| Volume | 39 |
| Issue number | 12 |
| DOIs | |
| State | Published - Sep 15 2012 |
Keywords
- Fuzzy assignment problem
- Genetic algorithm
- I L-metric
- Level effect function
- Markov chain
- U L-dispersion
Fingerprint
Dive into the research topics of 'Study on solution models and methods for the fuzzy assignment problems'. Together they form a unique fingerprint.Cite this
- APA
- Author
- BIBTEX
- Harvard
- Standard
- RIS
- Vancouver