A stochastic seaport network retrofit management problem considering shipping routing design

Abstract Seaports are exposed to various uncertain disasters caused by natural or human factors, which have multi-dimensional impacts on the economy. Retrofit appears as one of the effective mitigation methods to protect the seaport network and to reduce the post-disaster loss in the port management engineering. The post-disaster loss is quantified by replacement or repair cost of the structural damage and travel delay loss of vessels. Therefore, given a set of seaports, this paper aims to provide solutions for which seaports should be retrofitted in order to minimize the damage loss due to unpredictable disasters. We first present a network representation of a seaport shipping network. Based on the network, a two-stage stochastic programming model is formulated with a sub-model of the shipping routing design. Benders decomposition method is then used to solve the mixed-integer non-linear problem. Finally, we apply the two-stage model to solve the retrofit problem of eight mainline seaports in China Mainland. The real-time case study shows that the proposed model is efficient to get good solutions.

[1]  Kjetil Fagerholt,et al.  Ship routing and scheduling in the new millennium , 2013, Eur. J. Oper. Res..

[2]  Changzheng Liu,et al.  Highway Network Retrofit under Seismic Hazard , 2010 .

[3]  Zhuo Sun,et al.  Container routing in liner shipping , 2013 .

[4]  Hai Yang,et al.  Models and algorithms for road network design: a review and some new developments , 1998 .

[5]  Adolf K.Y. Ng,et al.  The Evolution and Research Trends of Port Geography , 2013 .

[6]  Stuart D. Werner.  Seismic Guidelines for Ports , 1998 .

[7]  Chang-Guk Sun,et al.  Real-time assessment framework of spatial liquefaction hazard in port areas considering site-specific seismic response , 2014 .

[8]  J. F. Benders.  Partitioning procedures for solving mixed-variables programming problems , 1962 .

[9]  David Ronen,et al.  Ship scheduling: The last decade , 1993 .

[10]  Xiangtong Qi,et al.  Minimizing fuel emissions by optimizing vessel schedules in liner shipping with uncertain port times , 2012 .

[11]  Masanobu Shinozuka,et al.  Simulation-based seismic loss estimation of seaport transportation system , 2009, Reliab. Eng. Syst. Saf..

[12]  Zaili Yang,et al.  A new risk quantification approach in port facility security assessment , 2014 .

[13]  Warren B. Powell,et al.  Stochastic Programming in Transportation and Logistics , 2003 .

[14]  Abdollah Shafieezadeh,et al.  Scenario-based resilience assessment framework for critical infrastructure systems: Case study for seismic resilience of seaports , 2014, Reliab. Eng. Syst. Saf..

[15]  D Ronen,et al.  CARGO SHIPS ROUTING AND SCHEDULING: SURVEY OF MODELS AND PROBLEMS. IN: MARITIME TRANSPORT , 1983 .

[16]  Changzheng Liu,et al.  A two-stage stochastic programming model for transportation network protection , 2009, Comput. Oper. Res..

[17]  Akio Imai,et al.  Multi-port vs. Hub-and-Spoke port calls by containerships , 2009 .

[18]  Henrik Andersson,et al.  Containership Routing and Scheduling in Liner Shipping: Overview and Future Research Directions , 2014, Transp. Sci..

[19]  Beate M. W. Ratter,et al.  Storm surge risk perception and resilience: A pilot study in the German North Sea coast , 2015 .

[20]  Anne S. Kiremidjian,et al.  Estimation of Downtime-Related Revenue Losses in Seaports following Scenario Earthquakes , 2004 .

[21]  Jin Wang,et al.  An integrated fuzzy risk assessment for seaport operations , 2014 .