The location-allocation model for multi-classification-yard location problem. (February 2019)

• Record Type: Journal Article
• Authors: Lin, Boliang; Liu, Siqi; Lin, Ruixi; Wang, Jiaxi; Sun, Min; Wang, Xiaodong; Liu, Chang; Wu, Jianping; Xiao, Jie
• Is Part Of: Transportation research. Volume 122(2019)
• Page Start: 283
• Page End: 308
• Publication Date: 2019-02
• Subjects: Classification yard -- Location-allocation problem -- Bi-level programming model -- Simulated annealing -- Rail network; Logistics -- Periodicals; Transportation -- Periodicals; 388.011
• DOI: 10.1016/j.tre.2018.12.013
• Languages: English
• ISSNs: 1366-5545

Abstract

Highlights: This paper constructs a bi-level programming model, the plan of no investment is incorporated and the capital recovery factor is introduced. An efficient and effective simulated annealing algorithm is proposed and applied for solving the model. A large-scale China railroad system, which is one of the largest railway networks in the world, is used to test our method. Abstract: This paper proposes a bi-level programming model for the multi-classification-yard location (MCYL) problem. The upper-level is intended to find an optimal establishment or improvement strategy for candidate nodes with a budget constraint, which is involved with the selection of potential yard locations and the determination of yard size and capacity. The lower-level aims to obtain the least costly plan of railcar reclassification considering yard classification capacity and tracks, on the basis of the strategy given by the upper-level. A simulated annealing (SA) algorithm is then applied to solve the MCYL problem of a large-scale China railway network.