A stochastic programming model for emergency supply planning considering traffic congestion. (3rd August 2019)

• Record Type: Journal Article
• Authors: Wang, Qingyi; Nie, Xiaofeng
• Is Part Of: IISE transactions. Volume 51:Number 8(2019)
• Page Start: 910
• Page End: 920
• Publication Date: 2019-08-03
• Subjects: Emergency supply planning -- traffic congestion effects -- BPR function -- generalized Benders decomposition; Industrial engineering -- Periodicals; Systems engineering -- Periodicals; Industrial engineering; Systems engineering; Electronic journals; Periodicals; 670.285
• DOI: 10.1080/24725854.2019.1589657
• Languages: English
• ISSNs: 2472-5854

Abstract

Abstract: Traffic congestion is one key factor that delays emergency supply logistics after disasters, but it is seldom explicitly considered in previous emergency supply planning models. To fill the gap, we incorporate traffic congestion effects and propose a two-stage location-allocation model that facilitates the planning of emergency supplies pre-positioning and post-disaster transportation. The formulated mixed-integer nonlinear programming model is solved by applying the generalized Benders decomposition algorithm, and the suggested approach outperforms the direct solving strategy. With a case study on a hurricane threat in the southeastern USA, we illustrate that our traffic congestion incorporated model is a meaningful generalization of a previous emergency supply planning model in the literature. Finally, managerial insights about the supplies pre-positioning plan and traffic control policy are discussed.