Tactical planning for dynamic technician routing and scheduling problems

The authors consider the tactical planning aspect of a dynamic technician routing and scheduling problem with a time horizon of several days. In this problem study, some tasks are known beforehand, while others arrive dynamically. The tactical planning is to schedule the known tasks, such that they minimize the overall driving distance while ensuring short service times for the dynamic tasks. Without tactical planning, the known tasks would be spread throughout the whole area as they are scheduled based on a first-come-first-serve principle. In this study, they partition the area into disjoint slices covering the full plane and then assign the slices to individual work days. The partitioning of the area will be constructed with a balanced sweep algorithm using two approaches: The first is based on a parallel sweep-line following a given angle, while the second is based on a rotating sweep-line around a given origin. To guide the partitioning, they aim to minimize the degree of dynamism, which in their case is defined by the number of dynamic tasks, the distance from known tasks to dynamic tasks, and the tightness of the time windows. The tactical planning is evaluated using real-life and synthetic clustered data, where some of the tasks are known beforehand, and some are dynamic. They benchmark the various partitioning approaches against the default strategy of serving all known tasks on a first-come-first-serve basis. Computational results are reported showing around a 10% reduction in driving distance when using tactical planning. Furthermore, they show that up to 70% of the technicians can have a non-dynamic work day, without a significant increase in driving distance.

• Record URL:
  • https://doi.org/10.1016/j.tre.2023.103225
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S1366554523002132
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13665545
• Supplemental Notes:
  • © 2023 The Authors. Published by Elsevier Ltd. Abstract reprinted with permission of Elsevier.
• Authors:
  • Chini Nielsen, Clara
  • Pisinger, David
  • 0000-0001-7695-9662
• Publication Date: 2023-9

Language

• English

Media Info

• Media Type: Web
• Features: Appendices; Figures; References; Tables;
• Pagination: 103225
• Serial:
  • Transportation Research Part E: Logistics and Transportation Review
  • Volume: 177
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1366-5545
  • Serial URL: http://www.sciencedirect.com/science/journal/13665545

Subject/Index Terms

• TRT Terms: Algorithms; Planning; Routing; Scheduling
• Subject Areas: Data and Information Technology; Highways; Planning and Forecasting;

Filing Info

• Accession Number: 01891149
• Record Type: Publication
• Files: TRIS
• Created Date: Aug 28 2023 9:19AM