The overview efficiency and effectiveness of an entire organization depends greatly on how well its resources are being utilized. Resources may include personnel, equipment, vehicles, space, warehouses, etc. Sufficient resources must be deployed to meet business demands as well as ensure all business, marketing and operational rules and constraints are satisfied.
Our AI Resource Allocation Engine makes use of a variety of advanced AI techniques, such as constraint programming, business rules, and genetic algorithms to intelligiently produce optimized resource allocation schedules and plans that precisely match target demands while satisfying all rules and constraints. Our AI technology also allows businesses to react to changes in workload demands or unexpected events through an intelligent dynamic rescheduling algorithm.
The following are some success stories of deployed AI resource allocation systems using our technologies:
Possession/Engineering Work Scheduling - After the merger with KCRC, MTRCL needed a single AI system to schedule and manage all engineering works across all railway lines. The AI Engine deployed in 2004 was enhanced and updated. AI allows MTRCL to perform more engineering works with its existing resources. [more]
Possession/Engineering Work Scheduling (2004) - AI is used to prioritize and schedule all engineering works in this busy subway system, while maximizing resource utilization and ensuring all safety and operational rules and regulations are followed. This projectis was performed in 2004 prior to the railway merger. A new version was later created in 2010 after the merger to handle the needs of all railway lines. [more]
Airport Bay/Stand Allocation - Stands are allocated daily using AI based on the flight schedule and operational constraints, which ensure airport safety and passenger convenience, and facilitate smooth operations for airlines and handling agents. AI automatically produce a daily plan and real-time rescheduling. [more]
Airport Check-in Counter/Desk Allocation - In 1994, to cope with increasing demand in the aging Kai Tak Airport terminal building, CAD used AI to optimize the allocation of check-in counters/desks. AI maximizes the utilization of airport facilities by optimizing the location and number of check-in counters assigned to each flight. [more]
Air Cargo Handling System - In 1995, to support the operations of the new Super Terminal 1, HACTL investigated the use of AI to optimize the scheduling and utilization of resources, such as space, manpower, conveyor belts, hoists, cranes, and decks to service containers of import and export flights. [more]
Container Terminal Berth Allocation - To optimize the utilization of valuable container vessel berth spaces, MTL explored the use of AI to automatically assign and allocate space based on demand, usage patterns, and operational and business rules and constraints. [more]