@inproceedings{97e7a46e76824fe88e0a6b31343e1404,
title = "Simulation-Based Optimization Tool for Field Service Planning",
abstract = "Many companies that deliver units to customer premises need to provide periodical maintenance and services on request by their field service technicians. A common challenge is to evaluate different design choices, related to staffing decisions, technician scheduling strategies, and technological improvements in order to make the system more efficient. This work provides a simulation-based optimization tool to support decision makers in tackling this challenging problem. The proposed framework relies on an optimization engine for the generation of the daily plans. A simulation component is used to evaluate the applicability of such plans by taking into account the stochastic factors. Furthermore, an interface manages the communication between these two components and allows a feedback loop between the simulator and the optimizer to achieve more robust plans. The applicability of the framework is demonstrated through a business case to evaluate different staffing decisions.",
author = "Castane, \{Gabriel G.\} and Helmut Simonis and Brown, \{Kenneth N.\} and Yiqing Lin and Cemalettin Ozturk and Michele Garraffa and Mark Antunes",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 2019 Winter Simulation Conference, WSC 2019 ; Conference date: 08-12-2019 Through 11-12-2019",
year = "2019",
month = dec,
doi = "10.1109/WSC40007.2019.9004869",
language = "English",
series = "Proceedings - Winter Simulation Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "1684--1695",
booktitle = "2019 Winter Simulation Conference, WSC 2019",
address = "United States",
}