Abstract
Home health care (HHC) companies provide the care service for the patients at their homes in order to help them recover from illness or injury. Since transportation cost is one of the largest operating costs in the daily activities of HHC company, it is crucial to optimize daily traveling routes of the HHC vehicles in order to reduce the transportation cost meanwhile improving the service quality to patients. However, transportation has serious impacts on the environment. Therefore, it compels managers of the HHC companies to pay more attention to CO\(_2\) emissions when designing the daily logistics activities. This study addresses a daily transportation problem of a HHC company with the constraints of synchronized visits and carbon emissions. In order to solve the studied problem, we develop an ant colony optimization (ACO) algorithm. The experimental results highlight the efficiency of the proposed ACO algorithm compared with the Gurobi solver with a time limit of 3600 s.
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Luo, H., Dridi, M., Grunder, O. (2020). Ant Colony Optimization Algorithm for a Transportation Problem in Home Health Care with the Consideration of Carbon Emissions. In: Idoumghar, L., Legrand, P., Liefooghe, A., Lutton, E., Monmarché, N., Schoenauer, M. (eds) Artificial Evolution. EA 2019. Lecture Notes in Computer Science(), vol 12052. Springer, Cham. https://doi.org/10.1007/978-3-030-45715-0_11
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