Abstract
Container ports serve as crucial logistics hubs in global supply chains, but navigating ships within such ports is complex due to restricted waterways. Tugboats play a critical role in ensuring safety and efficiency by escorting and towing ships under these conditions. However, the tugboat deployment and scheduling problem has received little attention. To fill the research gap, we propose a new research problem - the dynamic tugboat deployment and scheduling problem, in which not all requests are confirmed initially but dynamically confirmed over time and future tugging demands need to be anticipated when managing the utilization of tugboats. To formulate the problem, we propose an extended Markov decision process (MDP) that incorporates both reactive task assignment decisions and proactive tugboat waiting decisions, creating a reactive and proactive MDP. To solve the advanced MDP model efficiently for real-time decisions, we develop an anticipatory approximate dynamic programming method that incorporates appropriate task assignment and waiting strategies for deploying and scheduling a heterogeneous tugboat fleet and embed the method into an improved rollout algorithm to anticipate future scenarios. The effectiveness, efficiency, and performance sensitivity of the developed modeling and solution methods are demonstrated via extensive numerical experiments for the Singapore container port.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.