Random Fuzzy Cost-Profit Equilibrium Model for Locating a Discrete Service Enterprise
Document Type
Article
Publication Date
11-23-2017
Abstract
A transportation (automotive service) facility location problem is important in urban infrastructure planning and construction. To handle it, researchers have proposed a number of stochastic/random models for locating an automotive service enterprise. However, most of them fail to describe all kinds of uncertainty, e.g., data imprecision. By considering regional constraints, this work proposes a new random fuzzy cost-profit equilibrium model by using uncertainty data and management methods. It presents a hybrid algorithm integrating stochastic fuzzy simulation and particle swarm optimization to solve the location problem of an automobile service enterprise. In addition, since risk factors can impact a decision, this work conducts a risk performance analysis when locating an automotive service enterprise. A practical example is given to illustrate the proposed model and algorithm.
Identifier
85035764724 (Scopus)
Publication Title
IEEE Access
External Full Text Location
https://doi.org/10.1109/ACCESS.2017.2773578
e-ISSN
21693536
First Page
4387
Last Page
4394
Volume
6
Grant
51405075
Fund Ref
National Natural Science Foundation of China
Recommended Citation
Jia, Hongfei; Li, Qiang; Tian, Guangdong; Zhou, Mengchu; and Li, Zhiwu, "Random Fuzzy Cost-Profit Equilibrium Model for Locating a Discrete Service Enterprise" (2017). Faculty Publications. 9183.
https://digitalcommons.njit.edu/fac_pubs/9183
