A Study on Practical Operational Planning for Container Stowage Considering Work Loading Time and Weight Balance

Abstract

The stowage of containers from terminal yards onto ships is a highly complex task, characterized by numerous changing constraints, extensive stakeholder involvement, and the necessity to maintain both balanced loading and minimal loading time. Stakeholders impacted include shipping companies, container terminal operators, vessel captains, trucking providers, and yard managers. The importance of addressing this problem lies in the ongoing drive toward automation and labor reduction in container terminals. Currently, human planners are the bottleneck in creating effective stowage plans. While algorithms have been proposed to minimize container reshuffling operations within the yard, no existing solution addresses multiple ship loading plans that simultaneously ensure proper weight balance and minimize work time. This research adopts a transdisciplinary approach, integrating maritime logistics, operations research, and computer science methods. We employ the NSGA-based multi-objective optimization algorithm to generate a diverse Pareto set of solutions that consider weight balance and loading time. We propose a practical algorithm capable of producing stowage plans that match human-generated solutions in quality, reducing overall manual effort and contributing to the smartification of logistics. The contribution of this paper is the demonstration that automated planning can handle numerous dynamic constraints and produce stowage plans of equivalent human quality, ultimately paving the way for more efficient, automated container terminals. In our case study, we validated effectiveness by comparing algorithm-generated plans with those created by human planners, revealing a clear trade-off between loading time and weight balance.