化工学报 ›› 2023, Vol. 74 ›› Issue (11): 4645-4655.DOI: 10.11949/0438-1157.20230883
收稿日期:
2023-08-28
修回日期:
2023-11-05
出版日期:
2023-11-25
发布日期:
2024-01-22
通讯作者:
高小永
作者简介:
高小永(1985—),男,博士,副教授,x.gao@cup.edu.cn
基金资助:
Xiaoyong GAO1(), Dun LIU1, Chaodong TAN1, Feifei LI2
Received:
2023-08-28
Revised:
2023-11-05
Online:
2023-11-25
Published:
2024-01-22
Contact:
Xiaoyong GAO
摘要:
大规模维修任务的调度优化在实际生产过程中具有广泛的应用,例如煤层气井维修任务调度优化、修井作业调度和压裂作业调度等。该问题规模庞大且求解困难,是实时调度优化的难点和挑战。合理的大规模维修任务调度对于保障油气田平稳生产和降低成本具有重要意义。为了有效解决这一难题,提出了基于ALNS-TS的优化求解算法,并通过不同规模的案例验证了算法的有效性。实验结果显示,对于代表性的10、50和100个维修任务的案例,求解时间分别为0.03、8.33和74.32 s,都能在分钟级时间内给出合理的调度方案。随着问题规模增加,基于ALNS-TS的算法比传统算法更高效,并能找到目标函数值更低的更优解。
中图分类号:
高小永, 刘顿, 檀朝东, 李菲菲. 基于ALNS-TS的大规模维修任务调度优化快速求解算法[J]. 化工学报, 2023, 74(11): 4645-4655.
Xiaoyong GAO, Dun LIU, Chaodong TAN, Feifei LI. ALNS-TS based fast optimization algorithm for large-scale maintenance task scheduling[J]. CIESC Journal, 2023, 74(11): 4645-4655.
分数 | 描述 |
---|---|
经过破坏并修复后,算法得到了新的全局最优解 | |
经过破坏并修复后,尚未接受过的解中有比当前解更优的解存在 | |
经过破坏并修复后,尚未接受过的劣解中有比当前解更差但满足接受准则的解存在 | |
经过破坏并修复后,尚未接受过的劣解中有比当前解更差且不满足接受准则的解存在 |
表1 分数调整参数
Table 1 Score adjustment parameter
分数 | 描述 |
---|---|
经过破坏并修复后,算法得到了新的全局最优解 | |
经过破坏并修复后,尚未接受过的解中有比当前解更优的解存在 | |
经过破坏并修复后,尚未接受过的劣解中有比当前解更差但满足接受准则的解存在 | |
经过破坏并修复后,尚未接受过的劣解中有比当前解更差且不满足接受准则的解存在 |
维修任务数量/个 | 创建的节点数/个 | 修剪的节点数/个 | 求解时间/s |
---|---|---|---|
10 | 223 | 109 | 0.65 |
14 | 6935 | 3464 | 11.94 |
18 | 73237 | 36610 | 238.99 |
20 | 406611 | 203282 | 1685.91 |
表2 10、 14、 18和20个任务案例的精确算法求解结果
Table 2 Exact algorithmic solution results for 10, 14, 18 and 20 task cases
维修任务数量/个 | 创建的节点数/个 | 修剪的节点数/个 | 求解时间/s |
---|---|---|---|
10 | 223 | 109 | 0.65 |
14 | 6935 | 3464 | 11.94 |
18 | 73237 | 36610 | 238.99 |
20 | 406611 | 203282 | 1685.91 |
算法 | 10个任务的求解 结果/min | 20个任务的求解 结果/min | 30个任务的求解 结果/min | 60个任务的求解 结果/min | 80个任务的求解 结果/min | 100个任务的求解 结果/min |
---|---|---|---|---|---|---|
精确算法 | 38.00 | 36.90 | — | — | — | — |
遗传算法 | 38.00 | 59.20 | 184.00 | 263.70 | 293.10 | 366.30 |
蚁群算法 | 38.00 | 45.50 | 108.80 | 234.30 | 264.30 | 309.60 |
模拟退火算法 | 38.00 | 49.90 | 153.40 | 285.00 | 324.20 | 447.80 |
Gurobi求解器 | 38.00 | 40.20 | 103.10 | 235.10 | 328.40 | 414.50 |
本文提出算法 | 38.00 | 42.70 | 101.20 | 191.10 | 243.00 | 283.50 |
表3 求解方案的目标函数值对比
Table 3 Comparison of objective function values of the solution
算法 | 10个任务的求解 结果/min | 20个任务的求解 结果/min | 30个任务的求解 结果/min | 60个任务的求解 结果/min | 80个任务的求解 结果/min | 100个任务的求解 结果/min |
---|---|---|---|---|---|---|
精确算法 | 38.00 | 36.90 | — | — | — | — |
遗传算法 | 38.00 | 59.20 | 184.00 | 263.70 | 293.10 | 366.30 |
蚁群算法 | 38.00 | 45.50 | 108.80 | 234.30 | 264.30 | 309.60 |
模拟退火算法 | 38.00 | 49.90 | 153.40 | 285.00 | 324.20 | 447.80 |
Gurobi求解器 | 38.00 | 40.20 | 103.10 | 235.10 | 328.40 | 414.50 |
本文提出算法 | 38.00 | 42.70 | 101.20 | 191.10 | 243.00 | 283.50 |
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