Management of internal delivery vehicles in maritime container terminals

Maritime container terminals are complex infrastructures to manage in transportation industry due to their high degree of uncertainty arisen from the limited and changing information. The present paper addresses the operational management of the available internal delivery vehicles on the yard of a...

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Bibliographic Details
Published inProgress in artificial intelligence Vol. 7; no. 1; pp. 65 - 80
Main Authors López-Plata, Israel, Expósito-Izquierdo, Christopher, Melián-Batista, Belén, Moreno-Vega, J. Marcos
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2018
Springer Nature B.V
Subjects
Artificial Intelligence
Computational Intelligence
Computer Imaging
Computer Science
Containers
Control
Data Mining and Knowledge Discovery
Delivery scheduling
Marine terminals
Marine transportation
Mechatronics
Natural Language Processing (NLP)
Pattern Recognition and Graphics
Ports
Regular Paper
Robotics
Ship terminals
Synchronism
Time synchronization
Transportation industry
Vehicles
Vision
Maritime container terminal
Variable neighbourhood search
Internal delivery vehicle
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Summary:Maritime container terminals are complex infrastructures to manage in transportation industry due to their high degree of uncertainty arisen from the limited and changing information. The present paper addresses the operational management of the available internal delivery vehicles on the yard of a maritime container terminal under random changes in the simultaneous movement of import, export, and transit containers. The main goal of the presented problem is to optimize the usage of the available internal vehicles in terms of working time in scenarios where synchronization is required when accessing to the different pick-up and drop-off container locations. An efficient variable neighbourhood search is here proposed to dispatch, route, and schedule the existing vehicles while adapting their behaviour to both the arrival of new information and unforeseen changes in the existing information related to the environment under analysis. The computational experiments indicate the suitable performance of the proposed technique on a wide range of realistic scenarios.
ISSN:2192-6352
2192-6360
DOI:10.1007/s13748-017-0129-1