.png){kind=icon}
.png){kind=icon}
Return
Distributionally robust optimisation model for multi-objective hub location problem via considering ambiguousness
.png){kind=icon}
PRE
AI
DOI：10.1080/23249935.2022.2094494.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
We formulate a new multi-objective hub location problem by considering economic, customer satisfaction and environmental objectives. The economic objective includes loss cost in addition to transportation cost and hub construction cost. The environmental objective covers noise pollution cost and carbon emissions trading cost. The customer satisfaction objective is innovatively defined as the sum of the transportation time satisfaction and transportation quality satisfaction. Transportation costs, noise levels and carbon emissions are assumed as uncertain parameters. In practice, the probability distributions of uncertain parameters are often ambiguous. To characterise this ambiguity, we first construct an ambiguity set to propose a distributionally robust multi-objective hub location model and derive its safe approximation under mean and dispersion ambiguity set. Then, from the perspective of the government, a goal programming model is established. Finally, we apply the proposed model to design China's super logistics hub network to verify the model's validity and better performance.
Keywords:
Multi-objective hub location problem
distributionally robust optimisation
ambiguity set
safe approximation
goal programming
Journal
IF:
3.1
Papers:
927
Citations:
2.2K