Abstract
This papera describes a maintenance scheduling application, which was developed together with an industrial partner. This is a highly combinatorial decision process, to plan and schedule the work of a group of travelling repair technicians, which perform preventive and corrective maintenance tasks at customer locations. Customers are located both in urban areas, where many customers are in close proximity, and in sparsely populated rural areas, where the travel time between customer sites is significant. To balance the workload for the agents, we must consider both the productive working time, as well as the travel between locations. As the monolithic problem formulation is unmanageable, we introduce a problem decomposition into multiple sequential steps, that is compatible with current management practice. We present and compare different models for the solution steps, and discuss results on datasets provided by the industrial partner.
| Original language | English |
|---|---|
| Article number | 2060007 |
| Journal | International Journal on Artificial Intelligence Tools |
| Volume | 29 |
| Issue number | 3-4 |
| DOIs | |
| Publication status | Published - 1 Jun 2020 |
UCC Futures
- Artificial Intelligence and Data Analytics
Keywords
- Maintenance scheduling
- service planning
- travelling repair person
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