An integrated programming model for storage management and vehicle scheduling at container terminals
An integrated programming model for storage management and vehicle scheduling at container terminals
In this paper, we study the optimization of yard operations, which are critical for the terminal efficiency. A linear mixed integer programming (MIP) model is proposed for scheduling different types of equipment and planning the storage strategy in an integrated way. We also investigate a nonlinear mixed integer programming (NLMIP) model to reduce the number of constraints and the computational time. A set of numerical results are carried out for the comparison between the linear model and the nonlinear model. Finally, we propose a genetic algorithm for the MIP model to illustrate how large scale problems can be solved and to show the effect of different factors on the performances of the optimization model
integrated scheduling, container port terminal, mixed integer programming, genetic algorithm
13-27
Wu, Y.
e279101b-b392-45c4-b894-187e2ded6a5c
Luo, J.
c3143e78-c638-4287-9900-e03d6ecaa448
Zhang, D.
1c04f0f4-c07c-4671-8fd0-fa07a685fea2
Dong, M.
a45bca74-ba9e-418c-92c1-34b300cad4f3
June 2013
Wu, Y.
e279101b-b392-45c4-b894-187e2ded6a5c
Luo, J.
c3143e78-c638-4287-9900-e03d6ecaa448
Zhang, D.
1c04f0f4-c07c-4671-8fd0-fa07a685fea2
Dong, M.
a45bca74-ba9e-418c-92c1-34b300cad4f3
Wu, Y., Luo, J., Zhang, D. and Dong, M.
(2013)
An integrated programming model for storage management and vehicle scheduling at container terminals.
Research in Transportation Economics, 42 (1), .
(doi:10.1016/j.retrec.2012.11.010).
Abstract
In this paper, we study the optimization of yard operations, which are critical for the terminal efficiency. A linear mixed integer programming (MIP) model is proposed for scheduling different types of equipment and planning the storage strategy in an integrated way. We also investigate a nonlinear mixed integer programming (NLMIP) model to reduce the number of constraints and the computational time. A set of numerical results are carried out for the comparison between the linear model and the nonlinear model. Finally, we propose a genetic algorithm for the MIP model to illustrate how large scale problems can be solved and to show the effect of different factors on the performances of the optimization model
This record has no associated files available for download.
More information
Published date: June 2013
Keywords:
integrated scheduling, container port terminal, mixed integer programming, genetic algorithm
Organisations:
Southampton Business School
Identifiers
Local EPrints ID: 385815
URI: http://eprints.soton.ac.uk/id/eprint/385815
ISSN: 0739-8859
PURE UUID: 50c3f09a-ecda-4397-bf36-e64c89186747
Catalogue record
Date deposited: 15 Jan 2016 14:00
Last modified: 15 Mar 2024 03:20
Export record
Altmetrics
Contributors
Author:
J. Luo
Author:
D. Zhang
Author:
M. Dong
Download statistics
Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.
View more statistics
