基于智能算法的船舶分段堆场调度计划与优化

Block stockyard scheduling and optimizing based on an intelligent algorithm

分段的移动是船舶分段堆场调度中最主要的作业过程,而移动路径的优劣决定着分段堆场调度的效率和成本。论文通过综合考虑临时阻挡分段数量、平板车转向次数和移动距离对调度成本的影响,提出分段综合移动难度的评价标准,以此建立数学模型,并以分段综合移动难度为优化目标,利用遗传算法选择分段在堆场中停放位置的较优方案,运用禁忌搜索优化柔性出场时间分段的出场顺序,构建启发式规则来确定分段最优的进、出场路径。最后,利用某船厂的实际数据对模型进行实例验证和数值分析,结果表明,本文方法可以得到较优的堆场作业计划,实现堆场资源的高效利用。

Block stockyard is a major operation procedure in dispatching a ship block in a storage yard. The pros and cons of moving path determined the efficiency and the cost of the stockyard scheduling operation. This paper presented a synthetical evaluation criterion that considering obstructive blocks, fiat transporter turning times and moving distance which influenced the scheduling cost. A mathematical model was established based on this criterion with the aim of minimizing the synthetical degree of moving the block. A genetic algorithm was formulated to select the optimal storage positions for the inbound blocks. Tabu search was used to optimize the entrance order of the blocks with flexible entering times. A heuristic rule was constructed to confirm the optimum entering and leaving routes of the blocks. Finally, real data from a shipyard were used to test the numerical analysis used in the models. The results showed that the proposed algorithm was effective to solve the scheduling problem in shipbuilding yards.