上海交通大学学报

上海交通大学学报 >

2020 , Vol. 54 >Issue 12: 1278 - 1290

DOI: https://doi.org/10.16183/j.cnki.jsjtu.2019.146

考虑设备故障的鲁棒调度计划模板的建模优化

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  • 同济大学　机械与能源工程学院，上海 　201804
方佳(1996-)，女，江苏省常州市人，硕士生，研究方向为生产调度建模与优化．

收稿日期: 2019-05-27

  网络出版日期: 2020-12-31

基金资助

国家自然科学基金(61473211)

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Modeling and Optimization of Robust Scheduling Template Considering Equipment Failure

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  • School of Mechanical Engineering, Tongji University, Shanghai 201804, China

Received date: 2019-05-27

  Online published: 2020-12-31

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摘要

为了解决不确定环境下的飞机移动装配线调度问题，提出了依赖感知器的果蝇优化算法(PDFOA)，生成具有较强鲁棒性的模板装配计划．PDFOA在借鉴果蝇优化算法的基础上设计了窄域嗅觉搜索操作与窄域视觉搜索操作，对邻域解进行高效的搜索与筛选．同时，为了加强算法的全局搜索能力，设置了果蝇“知识记忆库”记录寻优过程．最后，在各作业规模的算例下通过抽样仿真实验将PDFOA与禁忌搜索、遗传算法以及免疫粒子群优化算法进行对比，验证了PDFOA的有效性．

关键词： 设备故障与修复; 果蝇优化算法; 前摄型调度; 抽样仿真; 鲁棒性模板计划

本文引用格式

方佳, 陆志强 . 考虑设备故障的鲁棒调度计划模板的建模优化[J]. 上海交通大学学报, 2020 , 54(12) : 1278 -1290 . DOI: 10.16183/j.cnki.jsjtu.2019.146

Abstract

In order to solve the scheduling problem of aircraft moving assembly line in uncertainty environment, this paper proposes a perceptron-dependent fruit fly optimization algorithm(PDFOA) to generate the assembly scheduling template with strong robustness. The proposed PDFOA, taking the fruit fly optimization algorithm as the basis, designs narrow-field osphresis-search operation and narrow-field vision-search operation which is helpful for searching and choosing neighborhood solutions. Simultaneously, the PDFOA sets up a memory library to enhance the global search ability. Finally, simulation experiments are conducted using different testing samples on different job scales. The proposed PDFOA is compared with tabu search, the genetic algorithm and the immune particle swarm optimization algorithm. The results demonstrate the effectiveness of the PDFOA.

Key words： failure and repair of equipments; fruit fly optimization algorithm; proactive scheduling; sampling simulation; robust baseline scheduling

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