Journal
IEEE ACCESS
Volume 6, Issue -, Pages 4387-4394Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/ACCESS.2017.2773578
Keywords
Data management; discrete event systems; facility location allocation; uncertainty data; optimization algorithm; modeling and simulation; stochastic fuzzy simulation; particle swarm optimization
Categories
Funding
- National Natural Science Foundation of China [51405075, 51775238]
- National Natural Science Foundation of China [51405075, 51775238]
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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.
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