期刊
INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH
卷 60, 期 10, 页码 3219-3236出版社
TAYLOR & FRANCIS LTD
DOI: 10.1080/00207543.2021.1916117
关键词
Maintenance; repair and operation; service resource scheduling; multi-objective optimisation; multiple on-site tasks; diverse service processes
资金
- Ministry of Science and Technology of the People's Republic of China [2018YFB1701400, 71473077]
- State Key Laboratory of Advanced Design andManufacturing for Vehicle Body, Hunan University [71775004]
- StateKey Laboratory of Construction Machinery [SKLCM201903]
This study proposes an integrated scheduling model for on-site MRO, considering different service processes, teams, and resources, decomposing the MRO service process into multiple subtasks. Experimental results show that the new algorithm can efficiently obtain high-quality scheduling solutions.
The previous studies on service resource scheduling for maintenance, repair and operation (MRO) ignore the diverse service processes from different complex equipment and the coordination of task scheduling and resource allocation, which is less realistic when multiple tasks exist. In this work, we propose an integrated scheduling model of distributed service resources for on-site MRO, which simultaneously considers different service processes, service teams and material resources. The MRO service process is decomposed into multiple subtasks with hierarchical relationships (dependency and independency). Within the duration of the subtask, all multi-skill technicians in service team stay together and material resources are delivered from service providers. Resource allocation and task scheduling are integrated to minimise the makespan, the excessive human resources and the cost performance index of material resources. Further, we introduce six classic multi-objective evolutionary algorithms (MOEAs) to solve the scheduling problem, in which a novel and practical encoding method mixed with integers and decimals is developed. The design-of-experiment (DOE) method is used to determine the optimal combination of crucial parameters. Finally, 20 benchmark instances of multiple MRO tasks are tested. Experiment results show MOEA/D-DU could obtain higher quality scheduling solutions with relatively low computational costs in the integrated scheduling model.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据