Prof Celio Mesquita

Military aviation faces risks of cargo unbalancing due to the urgency required on loading for rapid take-off and mission accomplishment, especially in times of crisis, armed conflict or public calamity. We model and solve the problem of planning the loading of an aircraft according to utility score, weight and balance principles, confer agility to pallet assembly under safety requirements, and also serving multiple bases in a tour of simultaneous Pickup and Delivery at intermediate airfields. This research result may be applicable by military and also by commercial companies in dynamic environments, especially on handling catastrophic events, sometimes as a government contractor. This problem encompasses four sub-problems: Air Palletization, Weight and Balance, Pickup and Delivery, and Sequencing. This hard problem, named Military Air Cargo Load Planning Problem, is mathematically modeled in real scenarios, using a standardized pallet, considering the possible presence of troops, ensures that torque and center of gravity constraints are obeyed, and each item is delivered to its destination. In our approach, we carry out experiments with a commercial solver, four well known meta-heuristics, and a proposed heuristic, on benchmarks based on statistical data from the Brazilian Air Force.

军事航空领域常因需满足快速起飞与任务执行的紧急装载要求，面临货运失衡风险，尤其在危机、武装冲突或公共灾难场景下。本研究针对依据效用得分、重量与平衡（Weight and Balance）原则规划航空器装载的问题开展建模与求解，在满足安全要求的前提下优化货盘组装灵活性，并支持在中途机场执行多基地同步取送货任务。本研究成果可应用于军事领域，也可被动态环境下的商业企业采用，尤其是在作为政府承包商处理灾难性事件时。该问题包含四个子问题：航空货盘化（Air Palletization）、重量与平衡、取送货规划以及排序调度。这一被称为军用航空货运装载规划问题（Military Air Cargo Load Planning Problem）的复杂难题，基于标准化货盘、结合可能存在的人员搭载场景，在真实场景下进行数学建模，确保满足扭矩与重心约束，并将每一件货物准确运抵其目的地。在本研究的方法框架中，我们基于巴西空军的统计数据构建基准测试集，使用商业求解器、四种经典元启发式算法（meta-heuristics）以及本文提出的启发式算法开展对比实验。