Metaheuristics for solving a multimodal home-healthcare scheduling problem
نویسندگان
چکیده
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. This work is partially funded by the Austrian Federal Ministry of Transport, Innovation and Technology (BMVIT) within the strategic programme I2VSplus under grant 826153 (CareLog). M. Prandtstetter, A. Rendl, J. Puchinger AIT Austrian Institute of Technology GmbH Mobility Department, Dynamic Transportation Systems Giefinggasse 2, 1210 Vienna, Austria E-mail: {matthias.prandtstetter | andrea.rendl | jakob.puchinger}@ait.ac.at G. Hiermann, G. R. Raidl Institute of Computer Graphics and Algorithms Vienna University of Technology Favoritenstraße 9–11/186, 1040 Vienna, Austria E-mail: [email protected] 2 Hiermann, Prandtstetter, Rendl, Puchinger, Raidl
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عنوان ژورنال:
- CEJOR
دوره 23 شماره
صفحات -
تاریخ انتشار 2015