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

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