| 摘 要: 针对现有电梯维修保养(维保)方案无法适应维保人员短缺及无法保障维保成本的问题,从考虑平衡员工工作负荷的角度出发,提出了一种基于多目标遗传算法的电梯维保路径规划方案。首先,在考虑任务优先级和多维保站点调度的基础上,建立多目标优化模型;其次,对传统编码方式和遗传算子进行修改,并利用多目标遗传算法对模型进行求解;最后,采用实例对方案进行验证,并对比分解法和全局法两种方案在实例中的应用结果。结果表明,当算法迭代次数相同时,分解法展现出更为出色的性能。相比于全局法,分解法节约了17.3%的成本,减少了49.7%的员工工作时长标准差,节约了26.6%的人力资源。该方法可为电梯维保路径规划提供有益参考。 |
| 关键词: 电梯;多目标优化;维保路径规划;优先级;多维保站点 |
|
中图分类号: TP18
文献标识码: A
|
| 基金项目: 国家自然科学基金项目(52075496,51505430) |
|
| Research on Elevator Maintenance Path Planning Method Based on Multi-Objective Genetic Algorithm |
|
WEI Yimin, FENG Wei
|
(Zhejiang Province's Key Laboratory of Reliability Technology f or Mechanical and Electronic Product, Zhejiang Sci-tech University, Hangzhou 310018, China)
yiminwei@126.com; 1351104250@qq.com
|
| Abstract: Aiming at the problems that existing elevator maintenance plans can neither adapt to the shortage of maintenance personnel nor guarantee the maintenance cost, and considering the balance of employee workloads, this paper proposes a maintenance path planning method for elevators based on a multi-objective genetic algorithm. Firstly, a multi-objective optimization model is established based on task priorities and multi-site maintenance scheduling considerations. Secondly, modifications are made to the traditional encoding methods and genetic operators, and a multi-objective genetic algorithm is used to solve the model. Finally, the proposed method is validated using real cases, and the application results of the decomposition method and the global method are compared in the real cases. Results show that with the same number of algorithm iterations, the decomposition method demonstrates better performance. Compared to the global method, the decomposition method saves 17.3% in costs, reduces the standard deviation of employee work duration by 49.7% , and saves 26.6% of human resources. The proposed method provides valuable insights for elevator maintenance path planning. |
| Keywords: elevator; multi-objective optimization; maintenance path planning; priority; multi-site maintenance |
