物料配送与线边存储集成决策模型与算法

以飞机移动装配线的物料供给为应用背景，将该过程抽象为一类物料配送与线边存储集成优化问题，在线边空间可共享和重复使用的环境下对物料的配送及物料在线边的存储两类子问题进行联合决策.以小车配送次数最小化为目标函数，建立集成优化数学模型.针对该模型，设计基于蚁群算法的混合启发式算法.该算法的核心思想为借助蚁群算法的全局搜索能力搜寻较优的物料组批方式，通过基于物料批次划分的解生成算法联合决策各物料的配送时刻和物料在线边空间的存放位置.为了进一步提高解的质量和求解成功率，在解码算法中嵌入物料摆放位置调整的修复算法，对物料的存储方案进行再优化.通过数值实验，证明了模型与算法的有效性.
Abstract: The material supply process was abstracted as an integrated optimization problem of material delivery and line-side storage by taking the material supply for aircraft moving assembly line as the application background. Joint decisions were made for two sub-problems of material delivery and line-side storage in the conditions where the line-side space is shareable and reusable. An integrated optimization mathematical model was established to minimize the number of deliveries. A hybrid heuristic based on ant colony optimization (HACO) was proposed to solve the model. The core mechanism of HACO was to seek the optimized composition of material batches by the global searching capability of ant colony optimization algorithm. A batch-based solution generating algorithm was adopted to jointly make decisions on delivery time and storage positions at the line-side space for each material. A repairing algorithm was embedded in the decoding process to re-optimize the storage scheme of materials in order to further enhance the quality and the success rate of solutions. The effectiveness of the model and algorithm was verified through numerical experiments.