Optimizing the utilization of berth space in a container yard has a direct impact to operations bottom line. Each additional container vessel that it can handle may add millions to revenue. Our optimization software not only captures business and operational rules and constraints, it also allows the user to perform what-if analysis and problem solving.
Using optimization and resource allocation technologies plus dynamic decision-making and problem solving-capabilities, we were able to show an increase in overall productivity and efficiency in the container yard.
Modern Terminals Limited is the longest established and one of the leading container terminal operators in Hong Kong, opening the territory's first purpose-built container terminal in September 1972. MTL owns and operates Terminals 1, 2 and 5, plus two berths at Terminal 8 (West). It employs approximately 1,200 people to provide 24 hours a day service, throughout the year. In 2000, it handled over 3 million TEUs (20-foot equivalent units)!
MTL owns and operates five main berths and one feeder berth where up to eight vessels can berth simultaneously. With rapid business growth, these berth spaces must be allocated very efficiently to maximize utilization.
MTL is already setting numerous service and performance records. For example, a record was set in November 1999, by handling 44.35 moves per crane hour. A productivity record of 207 container moves per berthing hour was set in February 2000. MTL was also the winner of the prestigious Hong Kong Productivity Council Productivity Award for Services 1999.
Striving for performance is not easy. In 1996, MTL commissioned us to design and develop an Artificial Intelligence (AI) pilot system to automatically assign and allocate berth space based on demand, usage patterns, and operational and business rules and constraints.
Combining advanced scheduling technology with constraint programming, we designed a multi-user application that captures all the rules and constraints related to berth allocation and its management. Our system produced allocation plans in seconds, compared with hours that are normally required if done manually. This system was implemented in C++ using state-of-the-art component technologies.
The system not only performs highly efficient allocation at a fraction of the time taken by humans, it also performs real-time problem solving to resolve operational problems such as delays, incorrect vessel schedules or details. This allows time-critical decisions to be made on the spot without any sacrifice to service quality and safety.