Configuring pallets for aircraft requires careful consideration of a diverse set of air cargo elementspallets, containers, and non-standard packages; a set of conveyance optionscontainers, pallets, boxes, aircraft cargo areas; and a set of operator specified preferences or priorities. Unfortunately, current capabilities do not successfully address the complex needs of pallet planning. Due to the configuration needs, weight difference, and varying sizes, the selection and assembly process to construct these pallets is time-consuming, error-prone, and inefficient. Cougaar Software, Inc. (CSI) proposes developing a Configured Airlift Load Building Tool (CALBT)an Artificial Intelligence enhanced software capability, with automated algorithms and planning tools for palletized cargo to render virtual prototypes of loads for aircraft for assembling them for transportation. CSIs aim is to develop a tool that has (1) high performance optimization engine for determining an optimized load configuration; (2) intuitive and simple user interfaces; (3) an open API allowing other programs or systems to access the loading optimization; and (4) technologies required for determining, capturing, and/or sensing cargo information, item identification, and cargo and cargo hold dimensions. Findings will provide a tool that significantly reduces airman disabilities and injuries and improves the efficiency of aerial port operations.multi-agent systems,artificial intelligence,Automated Load Planning,Palletized Cargo,Bin Packing Problem,Military Cargo Aircraft,Package Picking,spatial
