Abstract
The Liner Shipping Fleet Repositioning Problem (LSFRP) poses a large financial
burden on liner shipping firms. During repositioning, vessels are moved between
services in a liner shipping network. The LSFRP is characterized by chains of
interacting activities, many of which have costs that are a function of their
duration; for example, sailing slowly between two ports is cheaper than sailing
quickly. Despite its great industrial importance, the LSFRP has received
little attention in the literature. We show how the LSFRP can be solved
sub-optimally using the planner POPF and optimally with a mixed-integer
program (MIP) and a novel method called Temporal Optimization Planning (TOP).
We evaluate the performance of each of these techniques on a dataset of
real-world instances from our industrial collaborator, and show that automated
planning scales to the size of problems faced by industry.
burden on liner shipping firms. During repositioning, vessels are moved between
services in a liner shipping network. The LSFRP is characterized by chains of
interacting activities, many of which have costs that are a function of their
duration; for example, sailing slowly between two ports is cheaper than sailing
quickly. Despite its great industrial importance, the LSFRP has received
little attention in the literature. We show how the LSFRP can be solved
sub-optimally using the planner POPF and optimally with a mixed-integer
program (MIP) and a novel method called Temporal Optimization Planning (TOP).
We evaluate the performance of each of these techniques on a dataset of
real-world instances from our industrial collaborator, and show that automated
planning scales to the size of problems faced by industry.
| Originalsprog | Engelsk |
|---|---|
| Titel | ICAPS 2012, the 22nd International Conference on Automated Planning and Scheduling |
| Antal sider | 8 |
| Forlag | AAAI Press |
| Publikationsdato | 2012 |
| Sider | 279-287 |
| ISBN (Trykt) | ISBN 978-1-57735-562-5 |
| Status | Udgivet - 2012 |