TY - JOUR
T1 - Random Fuzzy Cost-Profit Equilibrium Model for Locating a Discrete Service Enterprise
AU - Jia, Hongfei
AU - Li, Qiang
AU - Tian, Guangdong
AU - Zhou, Mengchu
AU - Li, Zhiwu
N1 - Funding Information:
This work was supported by the National Natural Science Foundation of China under Grant 51405075 and Grant 51775238.
Publisher Copyright:
© 2013 IEEE.
PY - 2017/11/23
Y1 - 2017/11/23
N2 - 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.
AB - 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.
KW - Data management
KW - discrete event systems
KW - facility location allocation
KW - modeling and simulation
KW - optimization algorithm
KW - particle swarm optimization
KW - stochastic fuzzy simulation
KW - uncertainty data
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U2 - 10.1109/ACCESS.2017.2773578
DO - 10.1109/ACCESS.2017.2773578
M3 - Article
AN - SCOPUS:85035764724
SN - 2169-3536
VL - 6
SP - 4387
EP - 4394
JO - IEEE Access
JF - IEEE Access
ER -