.png){kind=icon}
.png){kind=icon}
Return
A two-stage robust hub location problem with accelerated Benders decomposition algorithm
.png){kind=icon}
OA
AI
DOI：10.1080/00207543.2021.1953179.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
In this paper, a two-stage robust optimisation is presented for an uncapacitated hub location problem in which demand is uncertain and the level of conservatism is controlled by an uncertainty budget. In the first stage, locations for establishing hub facilities were determined, and allocation decisions were made in the second stage. An accelerated Benders decomposition algorithm was used to solve the problem. Computational experiments showed better results in terms of number of iterations and computation time for Benders decomposition with Pareto-optimal cuts in comparison with the classical Benders decomposition algorithm. According to numerical analysis, it was concluded that increasing the uncertainty budget also increased total costs for more established hubs. To determine the uncertainty budget in an appropriate manner, a new expected aggregate function was introduced. The numerical studies demonstrated the usefulness of the proposed method in defining the appropriate uncertainty budget in the presence of uncertainty.
Keywords:
Two-stage robust
hub location problem
demand uncertainty
Benders decomposition algorithm
Pareto-optimal cut
Journal
IF:
7.3
Papers:
1.1W
Citations:
3.7W
View more organizations