@inproceedings{2b449043377c4cada7f5d401abdbdab5,
title = "Home healthcare worker scheduling: A group genetic algorithm approach",
abstract = "Home healthcare worker scheduling is a hard combinatorial problem concerned with the allocation of care tasks to healthcare givers at a minimal cost while considering healthcare service quality by striving to meet the time window restrictions specified by the patients. This paper proposes a group genetic algorithm (GGA) for addressing the scheduling problem. The approach utilizes the strengths of unique group genetic operators to effectively and efficiently address the group structure of the problem, providing good solutions within reasonable computation times. Computational results obtained show that the GGA approach is effective.",
keywords = "Group genetic algorithm, Home healthcare, Multi-objective optimization, Staff scheduling",
author = "M. Mutingi and C. Mbohwa",
year = "2013",
language = "English",
isbn = "9789881925107",
series = "Lecture Notes in Engineering and Computer Science",
pages = "721--725",
booktitle = "Proceedings of the World Congress on Engineering 2013, WCE 2013",
note = "2013 World Congress on Engineering, WCE 2013 ; Conference date: 03-07-2013 Through 05-07-2013",
}