@inproceedings{e345d319db1b427b8e039a4e14df8ed6,
title = "A fuzzy simulated evolution algorithm for multi-objective homecare worker scheduling",
abstract = "Due to ever-growing need for satisfactory homecare services in every society, development of efficient staff scheduling methods is crucial. Homecare services are aimed at providing medical, paramedical and social aid to patients at their own homes, leading to reduced hospitalization and healthcare operations costs in the medium to long term. However, the homecare staff scheduling problem is a complex one as it combines the hard vehicle routing and the staff assignment problems. This research presents a fuzzy simulated evolution algorithm, based on fuzzy evaluation, to address staff planning and scheduling in a home care environment. The objective is to decide (i) which patients to assign to each staff, and (ii) the best route or trip for each worker to execute the healthcare tasks, to satisfy the time window preferences of the patients. Results on illustrative experiments presented show that the approach is promising.",
keywords = "Homecare, fuzzy set theory, home healthcare, simulated evolution, staff scheduling, time windows",
author = "M. Mutingi and C. Mbohwa",
note = "Publisher Copyright: {\textcopyright} 2013 IEEE.; 2013 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2013 ; Conference date: 10-12-2013 Through 13-12-2013",
year = "2014",
month = nov,
day = "18",
doi = "10.1109/IEEM.2013.6962479",
language = "English",
series = "IEEE International Conference on Industrial Engineering and Engineering Management",
publisher = "IEEE Computer Society",
pages = "586--590",
booktitle = "IEEE International Conference on Industrial Engineering and Engineering Management",
address = "United States",
}