多目标智能优化的运输机群装载方案生成方法

Transport aircraft fleet load planning generation algorithmvia multi-objective intelligent optimization

运输机群装载方案制定是影响大规模航空运输任务成功实施的重要环节和核心要素。围绕异型、多架运输机的多样化物资装载规划需求,以安全、高效、经济性为装载规划目标,并以起飞重量、货舱尺寸、重心包线、舱段几何结构、舱段结构强度限制等实际限制条件为约束,建立了灵活、通用的多目标多约束装载规划数学模型;随后,围绕求解精度和规划速度的现实需求,提出多目标智能优化的运输机群装载方案生成算法,其内部嵌入了一个两阶段分步优化的种群搜索策略,在保证优化准确性的同时提升了方案生成速度;最后,通过想定多样化、多机型航空运输装载规划任务,并对比其他智能优化算法,结果表明,新方法所需架次少、规划效率高,具有很好的应用前景。

Transport aircraft fleet load planning is an important factor guiding the successful implementation of large-scale air transport missions.Aiming at the diversified material load planning requirements of different models and multiple transport aircrafts,a flexible and universal multi-objective and multi-constraint mathematical model is established with safety,efficiency and economy as the load planning goals,and with the actual conditions such as take-off weight,cargo hold space size,center of gravity envelope,geometry of the cargo hold segment,and cargo hold pressure limits as the constraints.Subsequently,by taking account of the realistic requirements of solving accuracy and planning speed,a multi-objective intelligent optimization transport aircraft fleet load planning generation algorithm is proposed.A two-stage and step-by-step optimization population search strategy is embedded in this algorithm,which improves the speed of scheme generation while ensuring the accuracy of optimization.Finally,by setting air transport loading planning tasks with diversified and multiple aircraft models and by comparing with the other intelligent optimization algorithms,the results show that the proposed method requires fewer flights and has high planning efficiency,so it has good application prospect.