Fleet sizing and vehicle routing for container transportation in a static environment

Busan is one of the busiest seaports in the world where millions of containers are handled every year. The space of the container terminal at the port is so limited that several small container yards are scattered in the city. Containers are frequently transported between the container terminal and...

Full description

Saved in:
Bibliographic Details
Published in:OR Spectrum 2004-03, Vol.26 (2), p.193-209
Main Authors: Koo, Pyung Hoi, Lee, Woon Seek, Jang, and Dong Won
Format: Article
Language:English
Subjects:
Algorithms
Automation
Containers
Experiments
Heuristic
Integer programming
Logistics
Operations research
Optimization
Ports
Routing
Scheduling
Studies
Systems development
Transportation terminals
Travel
Traveling salesman problem
Vehicles
Citations: Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Busan is one of the busiest seaports in the world where millions of containers are handled every year. The space of the container terminal at the port is so limited that several small container yards are scattered in the city. Containers are frequently transported between the container terminal and container yards, which may cause tremendous traffic problems. The competitiveness of the container terminal may seriously be aggravated due to the increase in logistics costs. Thus, there exist growing needs for developing an efficient fleet management tool to resolve this situation. This paper proposes a new fleet management procedure based on a heuristic tabu search algorithm in a container transportation system. The proposed procedure is aimed at simultaneously finding the minimum fleet size required and travel route for each vehicle while satisfying all the transportation requirements within the planning horizon. The transportation system under consideration is static in that all the transportation requirements are predetermined at the beginning of the planning horizon. An optimization model is constructed to obtain a fleet planning with minimum vehicle travel time and to provide a lower bound on the fleet size. Then, a tabu search based procedure is presented to construct a vehicle routing with the least number of vehicles.
ISSN:0171-6468
1436-6304
DOI:10.1007/s00291-003-0152-4