蚁群算法求解复杂集装箱装载问题

摘要

针对复杂集装箱装载问题(CLP),应用启发式信息与蚁群算法求解了最优装栽方案.首先,建立了复杂集装箱装载问题的数学模型,利用蚁群算法对解空间的强搜索能力、潜在并行性及可扩充性,结合三空间分解策略将布局空间依次分割;然后,装入满足约束条件的最优货物块,完成不同大小三维矩形货物的装载布局.在此基础上,设计了基于空间划分策略的蚁群算法.最后以700件货物装入40尺(12.025 m)高柜箱进行计算,结果表明该方法能提高集装箱的空间利用率,同时兼顾了多个装载约束条件,可应用性好.%In view of the complex Container Loading Problem ( CLP), the optimal loading plan with heuristic information and the ant colony algorithm was proposed. Firstly, a mathematical model was generated. Considering the strong search ability, potential parallelism and scalability of ant colony algorithm, the proposed algorithm was combined with the triple-tree structure to split the layout of space in turn. Then, the three-dimensional rectangular objects of different sizes were placed to the layout space under the constraints. An ant colony algorithm based on spatial partition was designed to solve the optimal procedure. Finally, a design example that 700 pieces of goods were loaded into a 40-foot ( 12. 025 m) high cubic was calculated. The experimental results show that the proposed method can enhance the utilization of the container and it has a strong practicality.