改进自适应蚁群算法求解集装箱装载瓦楞纸板问题

集装箱装载瓦楞纸板问题是一个复杂组合优化问题,针对该问题,在满足基本的装载要求和约束条件下,充分利用自适应蚁群算法的强搜索能力和启发式算法对具体问题的针对性,将自适应蚁群算法和启发式算法结合,提出一种改进的自适应蚁群算法,求解出了最优装载方案。对纸板装载问题建立模型,提出目标函数并给出约束条件;根据实际情况提出启发式规则,将其与自适应蚁群算法进行结合;使用实例进行仿真验证。将仿真结果与实际情况进行对比,装载体积率明显提高,证明了该算法能够提高瓦楞纸板装载空间利用率,节省了人力,大大提高了工作效率。

Improved adaptive ant colony algorithm for container loading corrugated board problem

The problem of container loading corrugated board is a complex combinatorial optimization problem.Aiming at this problem,under the basic loading requirements and constraints,this paper makes full use of the strong searching ability of adaptive ant colony algorithm and heuristic algorithm is targeted to specific problems.Combining the ant colony algorithm with the heuristic algorithm,an improved adaptive ant colony algorithm is proposed to solve the optimal loading scheme.Modelling the cardboard loading problem,propose the objective function and give constraints,heuristic rules are proposed according to the actual situation and combined with the adaptive ant colony algorithm,use the example for simulation verification.The simulation results are compared with the actual situation and the loading volume rate shows a significant improvement,which proves that the algorithm can improve the utilization of corrugated board loading space,save manpower and greatly improve work efficiency.