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Abstract
The dynamic Technician Routing and Scheduling Problem (TRSP) is a challenging problem in the field service sector, particularly as companies strive to optimise operations with complex, real-world constraints. This dissertation focuses on routing optimisation and aims at improving the efficiency and effectiveness of mobile workforce management. The research addresses key challenges at tactical, operational, and strategic levels, offering a comprehensive approach to the TRSP.
At the tactical level, this dissertation introduces methods for partitioning service areas into efficient clusters of tasks, ensuring that both known and dynamic tasks can be assigned to technicians. These methods improve task allocation by reducing travel times and balancing workloads across service regions, leading to better schedules and enhanced routing efficiency, directly impacting operational performance and streamlining field operations.
At the operational level, solutions are developed for better utilisation of technicians by introducing skill substitution and balancing workload. This includes addressing the dynamic nature of tasks and incorporating real-world complexities such as technician home locations and task urgencies. The operational models demonstrate significant potential for improving service levels and technician satisfaction, as well as general operational efficiency.
At the strategic level, the dissertation proposes a novel framework for workforce investment planning, integrating actual routing solutions into the decision-making process to make more informed and effective investments. This approach offers flexibility in investment decisions, allowing for the optimisation of workforce size, skill sets, and deployment strategies. The strategic insights gained from this research support long-term planning and sustainable growth in field service operations.
The optimisation approaches have been shaped to tackle real-world challenges utilising actual industry data from TDC-NET, Denmark’s leading infrastructure provider. The findings demonstrate substantial improvements in reducing driving distances and increasing operational efficiency of mobile workforce management, supporting sustainability development goals (SDGs) and laying the foundation for more advanced planning tools in the field service sector.
Overall, this dissertation bridges the gap between theoretical optimisation and practical application, providing a framework for enhancing service operations and workforce planning. This framework will promote innovation in the industry and lay the foundation for further advancements in efficient mobile workforce management and rouitng.
At the tactical level, this dissertation introduces methods for partitioning service areas into efficient clusters of tasks, ensuring that both known and dynamic tasks can be assigned to technicians. These methods improve task allocation by reducing travel times and balancing workloads across service regions, leading to better schedules and enhanced routing efficiency, directly impacting operational performance and streamlining field operations.
At the operational level, solutions are developed for better utilisation of technicians by introducing skill substitution and balancing workload. This includes addressing the dynamic nature of tasks and incorporating real-world complexities such as technician home locations and task urgencies. The operational models demonstrate significant potential for improving service levels and technician satisfaction, as well as general operational efficiency.
At the strategic level, the dissertation proposes a novel framework for workforce investment planning, integrating actual routing solutions into the decision-making process to make more informed and effective investments. This approach offers flexibility in investment decisions, allowing for the optimisation of workforce size, skill sets, and deployment strategies. The strategic insights gained from this research support long-term planning and sustainable growth in field service operations.
The optimisation approaches have been shaped to tackle real-world challenges utilising actual industry data from TDC-NET, Denmark’s leading infrastructure provider. The findings demonstrate substantial improvements in reducing driving distances and increasing operational efficiency of mobile workforce management, supporting sustainability development goals (SDGs) and laying the foundation for more advanced planning tools in the field service sector.
Overall, this dissertation bridges the gap between theoretical optimisation and practical application, providing a framework for enhancing service operations and workforce planning. This framework will promote innovation in the industry and lay the foundation for further advancements in efficient mobile workforce management and rouitng.
Original language | English |
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Publisher | Technical University of Denmark |
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Number of pages | 160 |
Publication status | Published - 2024 |
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Dive into the research topics of 'Tactical routing and scheduling optimisation for dynamic field service'. Together they form a unique fingerprint.Projects
- 1 Finished
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Robust Routing Optimisation for Field Service
Nielsen, C. C. (PhD Student), Pisinger, D. (Main Supervisor), Røpke, S. (Supervisor), Pantuso, G. (Examiner) & Toth, P. (Examiner)
01/09/2021 → 14/01/2025
Project: PhD