A stochastic seaport network retrofit management problem considering shipping routing design. (January 2016)

• Record Type: Journal Article
• Authors: Peng, Yun; Wang, Wenyuan; Guo, Zijian; Song, Xiangqun; Zhang, Qi
• Is Part Of: Ocean & coastal management. Volume 119(2016)
• Page Start: 169
• Page End: 176
• Publication Date: 2016-01
• Subjects: Seaport management -- Stochastic programming -- Network retrofit -- Shipping routing design; Marine resources -- Management -- Periodicals; Coastal zone management -- Periodicals; Coastal ecology -- Periodicals; Ressources marines -- Périodiques; Littoral -- Aménagement -- Périodiques; Écologie littorale -- Périodiques; Coastal ecology; Coastal zone management; Marine resources -- Management; Periodicals; Electronic journals; 551.46
• DOI: 10.1016/j.ocecoaman.2015.10.013
• Languages: English
• ISSNs: 0964-5691

Abstract

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. Highlights: Retrofit appears as one of the effective mitigation methods to reduce the post-disaster loss. This paper aims to provide solutions for which seaports should be retrofitted. A two-stage stochastic programming model is formulated to minimize the damage loss due to unpredictable disasters. Benders decomposition method is used to solve the mixed-integer non-linear problem.