TY - JOUR
T1 - Stochastic service network design with rerouting
AU - Bai, Ruibin
AU - Wallace, Stein W.
AU - Li, Jingpeng
AU - Chong, Alain Yee Loong
N1 - Funding Information:
This work is supported by National Natural Science Foundation of China (Grant No. 71001055 ) and Zhejiang Provincial Natural Science Foundation (Grant No. Y1100132 ). We are also grateful for the financial support by Ningbo Science and Technology Bureau through Project 2012B10055.
PY - 2014/2
Y1 - 2014/2
N2 - Service network design under uncertainty is fundamentally crucial for all freight transportation companies. The main challenge is to strike a balance between two conflicting objectives: low network setup costs and low expected operational costs. Together these have a significant impact on the quality of freight services. Increasing redundancy at crucial network links is a common way to improve network flexibility. However, in a highly uncertain environment, a single predefined network is unlikely to suit all possible future scenarios, unless it is prohibitively costly. Hence, rescheduling is often an effective alternative. In this paper, we proposed a new stochastic freight service network design model with vehicle rerouting options. The proposed model explicitly introduces a set of integer variables for vehicle rerouting in the second stage of the stochastic program. Although computationally more expensive, the resultant model provides more options (i.e. rerouting) and flexibility for planners to deal with uncertainties more effectively. The new model was tested on a set of instances adapted from the literature and its performance and characteristics are studied through both comparative studies and detailed analyses at the solution structure level. Implications for practical applications are discussed and further research directions are also provided.
AB - Service network design under uncertainty is fundamentally crucial for all freight transportation companies. The main challenge is to strike a balance between two conflicting objectives: low network setup costs and low expected operational costs. Together these have a significant impact on the quality of freight services. Increasing redundancy at crucial network links is a common way to improve network flexibility. However, in a highly uncertain environment, a single predefined network is unlikely to suit all possible future scenarios, unless it is prohibitively costly. Hence, rescheduling is often an effective alternative. In this paper, we proposed a new stochastic freight service network design model with vehicle rerouting options. The proposed model explicitly introduces a set of integer variables for vehicle rerouting in the second stage of the stochastic program. Although computationally more expensive, the resultant model provides more options (i.e. rerouting) and flexibility for planners to deal with uncertainties more effectively. The new model was tested on a set of instances adapted from the literature and its performance and characteristics are studied through both comparative studies and detailed analyses at the solution structure level. Implications for practical applications are discussed and further research directions are also provided.
KW - Rerouting
KW - Service network design
KW - Stochastic programming
KW - Transportation logistics
UR - http://www.scopus.com/inward/record.url?scp=84891078471&partnerID=8YFLogxK
U2 - 10.1016/j.trb.2013.11.001
DO - 10.1016/j.trb.2013.11.001
M3 - Article
AN - SCOPUS:84891078471
SN - 0191-2615
VL - 60
SP - 50
EP - 65
JO - Transportation Research, Series B: Methodological
JF - Transportation Research, Series B: Methodological
ER -