A practical scheduling method is developed and implemented to determine the optimal allocation of technicians to candidate tour types and start times in a field service environment. Historical data is aggregated to determine a weekly work volume distribution and technician availability profile. These and other quantitative factors populate a mixed integer programming model for determining the distribution of technician tours that will minimize queueing delay in completing service, subject to side constraints on tour type quantities. The approach has been successfully implemented to schedule installation and maintenance technicians at a major telecommunication service provider and could easily be adapted to other operational contexts.
Published in | American Journal of Engineering and Technology Management (Volume 2, Issue 6) |
DOI | 10.11648/j.ajetm.20170206.11 |
Page(s) | 77-82 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
Copyright |
Copyright © The Author(s), 2017. Published by Science Publishing Group |
Scheduling, Mixed Integer Linear Programming, Operations Management
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APA Style
Dennis Charles Dietz. (2017). Optimal Scheduling for a Service Technician Workforce with Time-varying Work Volume and Technician Availability. American Journal of Engineering and Technology Management, 2(6), 77-82. https://doi.org/10.11648/j.ajetm.20170206.11
ACS Style
Dennis Charles Dietz. Optimal Scheduling for a Service Technician Workforce with Time-varying Work Volume and Technician Availability. Am. J. Eng. Technol. Manag. 2017, 2(6), 77-82. doi: 10.11648/j.ajetm.20170206.11
AMA Style
Dennis Charles Dietz. Optimal Scheduling for a Service Technician Workforce with Time-varying Work Volume and Technician Availability. Am J Eng Technol Manag. 2017;2(6):77-82. doi: 10.11648/j.ajetm.20170206.11
@article{10.11648/j.ajetm.20170206.11, author = {Dennis Charles Dietz}, title = {Optimal Scheduling for a Service Technician Workforce with Time-varying Work Volume and Technician Availability}, journal = {American Journal of Engineering and Technology Management}, volume = {2}, number = {6}, pages = {77-82}, doi = {10.11648/j.ajetm.20170206.11}, url = {https://doi.org/10.11648/j.ajetm.20170206.11}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajetm.20170206.11}, abstract = {A practical scheduling method is developed and implemented to determine the optimal allocation of technicians to candidate tour types and start times in a field service environment. Historical data is aggregated to determine a weekly work volume distribution and technician availability profile. These and other quantitative factors populate a mixed integer programming model for determining the distribution of technician tours that will minimize queueing delay in completing service, subject to side constraints on tour type quantities. The approach has been successfully implemented to schedule installation and maintenance technicians at a major telecommunication service provider and could easily be adapted to other operational contexts.}, year = {2017} }
TY - JOUR T1 - Optimal Scheduling for a Service Technician Workforce with Time-varying Work Volume and Technician Availability AU - Dennis Charles Dietz Y1 - 2017/11/07 PY - 2017 N1 - https://doi.org/10.11648/j.ajetm.20170206.11 DO - 10.11648/j.ajetm.20170206.11 T2 - American Journal of Engineering and Technology Management JF - American Journal of Engineering and Technology Management JO - American Journal of Engineering and Technology Management SP - 77 EP - 82 PB - Science Publishing Group SN - 2575-1441 UR - https://doi.org/10.11648/j.ajetm.20170206.11 AB - A practical scheduling method is developed and implemented to determine the optimal allocation of technicians to candidate tour types and start times in a field service environment. Historical data is aggregated to determine a weekly work volume distribution and technician availability profile. These and other quantitative factors populate a mixed integer programming model for determining the distribution of technician tours that will minimize queueing delay in completing service, subject to side constraints on tour type quantities. The approach has been successfully implemented to schedule installation and maintenance technicians at a major telecommunication service provider and could easily be adapted to other operational contexts. VL - 2 IS - 6 ER -