A robust hub location model for disaster response via stochastic programming

2013 ◽  
pp. 253-258
Keyword(s):  
Stochastic Programming ◽  
Disaster Response ◽  
Location Model ◽  
Hub Location

Network Planning Location Model for China Railway Express

2019 ◽  
Vol 2673 (2) ◽  
pp. 263-274 ◽  
Author(s):  
Yuehui Wu ◽  
Chang Lin ◽  
Jingyu Huang
Keyword(s):  
Network Planning ◽  
Location Model ◽  
Hub Location ◽  
Transportation Mode ◽  
Hub And Spoke ◽  
Organization Mode ◽  
China Railway ◽  
Transportation Organization ◽  
Further Development

With the gradual implementation of the Belt & Road Initiative, China Railway Express (CRExpress) has gradually gained support as an important transportation mode between China and Europe. However, the high cost of operation, caused by the unscientific organization mode and the small quantity of returning cargo, hinders the further development of CRExpress. Prior studies have shown that applying the hub-and-spoke transportation organization mode to the CRExpress system could decrease operational cost effectively. To carry out network planning for CRExpress, based on its present situation and properties, a conventional hub location model is adjusted. The network planning location model for CRExpress which minimizes total operation cost and allows direct transportation mode is proposed as well as an algorithm based on the genetic algorithm (GA) approach. The reasonableness and feasibility of the model and algorithm are investigated and verified through a case study based on the CRExpress system. The result indicates that Chengdu, Yingkow, and Zhengzhou are selected as consolidation centers whereas Urumqi and Xining adopt direct transportation mode.

scholarly journals A Stochastic Programming Approach for Resilient Hub Location in Power Projection Network considering Random Hub Failures

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xu-Tao Zhang ◽  
Hai-Ling Bi ◽  
Yun Wang
Keyword(s):  
Stochastic Programming ◽  
Programming Model ◽  
Programming Approach ◽  
Hub Location ◽  
Hub Location Problem ◽  
Power Projection ◽  
Critical Facilities ◽  
Resilient Networks ◽  
The Impact ◽  
Projection Network

Hubs are critical facilities in the power projection network. Due to the uncertainty factors such as terrorism threats, severe weather, and natural disasters, hub facilities may be disrupted randomly, which could lead to excessive cost or loss in practice. One of the most effective ways to withstand and reduce the impact of disruptions is designing more resilient networks. In this paper, a stochastic programming model is employed for the hub location problem in the presence of random hub failures. A heuristic algorithm based on Monte Carlo method and tabu search is put forward to solve the model. The proposed approach is more general if there are numbers of hubs that would fail even with different failure probability. Compared with the benchmark model, the model which takes the factor of stochastic failure of hubs into account can give a more resilient power projection network.

scholarly journals A bi-objective hierarchical hub location model with facility failure

2018 ◽  
Vol 0 (0) ◽  
pp. 0-0
Author(s):  
Mohsen Babashahi ◽  
Kamran Shahanaghi ◽  
Mohammad Reza Gholamian ◽  
Arash Yavari
Keyword(s):  
Location Model ◽  
Hub Location

Multiple Allocation Hub Location Model with Fixed Arc Costs

2014 ◽  
Vol 47 (1) ◽  
pp. 73-96 ◽  
Author(s):  
Morton E. O'Kelly ◽  
James F. Campbell ◽  
Ricardo S. de Camargo ◽  
Gilberto de Miranda
Keyword(s):  
Location Model ◽  
Hub Location ◽  
Multiple Allocation

scholarly journals An Integrated Problem of p-Hub Location and Revenue Management with Multiple Capacity Levels under Disruptions

2019 ◽  
Vol 2019 ◽  
pp. 1-14
Author(s):  
Yan-Ting Hou ◽  
Jia-Zhen Huo ◽  
Feng Chu
Keyword(s):  
Stochastic Programming ◽  
Revenue Management ◽  
Programming Model ◽  
Profit Maximization ◽  
Transportation Cost ◽  
Sample Average Approximation ◽  
Management Problem ◽  
Hub Location ◽  
Two Stage ◽  
Airline Tickets

This paper considers an integrated hub location and revenue management problem in which a set of capacities is available from which one can be chosen for each hub and the disruption is considered in a star-star shaped airline network. We propose a two-stage stochastic programming model to maximize the profit of the network in which the cost of installing the hubs at different levels of capacities, the transportation cost, and the revenue obtained by selling airline tickets are considered. To provide flexible solutions, a hybrid two-stage stochastic programming-robust optimization model is developed by putting relative emphasis on a weighted sum of profit maximization. Furthermore, a sample average approximation approach is used for solving the stochastic programming formulation and a genetic algorithm approach is applied for both formulations. Numerical experiments are conducted to verify the mathematical formulations and compare the performance of the used approaches.

Sign in / Sign up

Export Citation Format

Share Document