Resource Allocation

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:

  • MTR Logo Hong Kong MTR
    Possession/Engineering Work Scheduling
    MTR carries 2.4 million passengers daily, making it one of the busiest in the world. Despite the large traffic-flow, the MTR has set for itself a very high service quality standard - train punctuality and delivery must be 99% and 99.5% on time respectively. To ensure these standards are met, the scheduling of engineering works must be optimized so that all necessary maintenance tasks are done in a timely manner. Through the use of AI techniques, we were able to help the subway streamline their scheduling/rescheduling processes and maximize their resource utilization, while providing early identification of potential violations of safety and operational regulations and guidelines for all scheduled engineering works. In addition, valuable domain knowledge and expertise related to these regulations and guidelines are now quantified, coded and preserved within the organization, for use by this and other systems. [more...]

  • AA Logo Hong Kong Airport Authority
    Airport Bay/Stand Allocation
    The Hong Kong International Airport has facilities to handle over 35 million passengers and 3 million tones of air cargo annually. Efficient use of these resources is crucial and critical to achieving the required throughput and service commitments of HKIA. The most important resource at the airport is, of course, the aircraft parking stands. Aircraft stands are allocated daily based on the flight schedule and a set of intricate operational constraints. These constraints ensure airport safety and passenger convenience, and facilitate smooth operations for airlines and handling agents. Our Stand Allocation System (SAS) is a mission critical system designed for non-stop 24-hour daily operations. Our AI Scheduling Engine consists for custom designed scheduling/rescheduling algorithms using AI constraint programming technology. [more...]

  • CAD Logo Hong Kong Civil Aviation Department
    Airport Check-in Counter/Desk Allocation
    In 1994, CAD had to turn down thousands of flight requests per year due to limited airport resources. The aging airport had a small terminal building that was already over congested. Although air traffic was on the increase, facilities in the passenger terminal building was fixed and limited. In order to service more flights and more passengers, resources such as check-in counters must be allocated very efficiently. The daily assignments of check-in counters to airlines and handling agents were the responsibility of CAD. This assignment is based on the daily flight schedule, usage patterns and statistics, and a set of operational and business rules, constraints and parameters. The problem complexity made it very difficult for a human to produce an optimal plan. Moreover, the manual process was too time-consuming to be effective. In order to cope with an increasing amount of passengers using the airport, CAD decided to implement an automated solution in late 1994. The Computerized Check-in Counter Allocation System (CCCAS) maximizes the utilization of airport facilities by optimizing the location and number of check-in counters assigned to each flight. We uniquely combined computer simulation with advanced constraint-based optimization techniques, provided by our AI Scheduling Engine, to produce a highly efficient scheduling algorithm. [more...]

  • HACTL Logo Hong Kong Air Cargo Terminals Ltd
    Air Cargo Handling System
    In 1995, HACTL started to investigate how the next generation resource allocation system should be designed and built to support its huge new air cargo handling facility, Super Terminal 1 at the new Chek Lap Kok International Airport. The new SuperTerminal 1 was designed to handle 2.6 million tones of air cargo yearly, which will meet the business needs in Hong Kong and Southern China well into the next decade. Therefore HACTL needed effective scheduling methodologies to support its new Super Terminal 1 operations. Our scheduling methodology based on advanced constraint-programming and object technology. A prototype system was developed to demonstrate the feasibility of the methodology using a scaled-down version of the new Super Terminal 1. This prototype assigns resources such as conveyor belts, hoists, cranes, and decks to service containers of import and export flights. The system performs scheduling based upon expected number of containers and the resources required by each flight. This scheduling system also performs real-time reactive scheduling to accommodate changes in allotment and resource availability. We also applied the proposed scheduling methodology to produce a design for a workspace and personnel scheduling system. The systems allocate suitable work areas for the build-up or the break-up of each container and a team of workers to perform these tasks based on operational constraints and criteria. [more...]

  • MTL Logo Modern Terminals Ltd
    Container Terminal Berth Allocation
    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. 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. [more...]