Jurong Port is developing the next generation multipurpose port by offering a full range of high-value maritime port services. Stevedore Management Center (SMC) was set up to supplement stevedore labor requirements and works closely with the stevedore companies to manage and locate labor.
The complexity of SMC operations make it necessary to develop a strategic plan to assist workforce renewal (hiring and training needs) to ensure long term sustainability of the stevedore workforce serving the maritime industry.
Today SMC is using excel spreadsheet for rostering and planning of the stevedore supplementary workforce. Some of the challenges faced include the uncertainty in the arrival time of the vessels, workers reporting sick and the relatively short time frame to finalize the detailed deployment plan.
In this project, we consider a robust optimization approach to optimize the scheduling of the stevedore workforce in relation to business goals, such as minimizing port stay or deployment cost. Our model factors in the many constraints in manpower requirements and legal restrictions, scheduling flexibility, and vessel and cargo limitations, as well as uncertainties, such as weather conditions, vessel arrival times and manpower productivity. We propose a novel formulation to track berth time within the scheduling task, as such, allowing us to resolve the uncertainty despite the mixed-integer structure of the model. The uncertainty sets were also constructed using real world data and planning norms.
The deployment of our model will not just result in more efficient and adaptive deployment of stevedore manpower, but also savings in time and cost through automating the planning process. Using our model as leverage, the project has also sparked greater efforts in Jurong Port to collect more data that would help the estimation of worker productivity.
Project Title: Workforce Planning and Scheduling Optimization
Done By: Jurong Port Pte Ltd, National University of Singapore (NUS) and Singapore Data Science Consortium (SDSC)
Contact Person: Prof. James Pang, Associate Professor, Department of Analytics and Operations, NUS Business School
This research is supported by the National Research Foundation, Prime Minister’s Office, Singapore under its Industry Alignment Fund (Pre-positioning) Funding Initiative.