Metaheuristics for solving a multimodal home-healthcare scheduling problem

Gerhard Hiermann, Matthias Prandtstetter (), Andrea Rendl (), Jakob Puchinger () and Günther Raidl ()

Central European Journal of Operations Research, 2015, vol. 23, issue 1, 89-113

Abstract: We present a general framework for solving a real-world multimodal home-healthcare scheduling (MHS) problem from a major Austrian home-healthcare provider. The goal of MHS is to assign home-care staff to customers and determine efficient multimodal tours while considering staff and customer satisfaction. Our approach is designed to be as problem-independent as possible, such that the resulting methods can be easily adapted to MHS setups of other home-healthcare providers. We chose a two-stage approach: in the first stage, we generate initial solutions either via constraint programming techniques or by a random procedure. During the second stage, the initial solutions are (iteratively) improved by applying one of four metaheuristics: variable neighborhood search, a memetic algorithm, scatter search and a simulated annealing hyper-heuristic. An extensive computational comparison shows that the approach is capable of solving real-world instances in reasonable time and produces valid solutions within only a few seconds. Copyright Springer-Verlag Berlin Heidelberg 2015

Keywords: Home health care; Vehicle routing; Optimization; Metaheuristics (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (36)

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DOI: 10.1007/s10100-013-0305-8

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