Abstract
The Instituto Mexicano del Seguro Social (IMSS) is the federal government medical institution with many hospitals around the country. Usually, the surgical operating areas within hospitals are constantly requested for emergency surgeries which trigger continuous changes in the established schedule, and having an effect in other factors such as doctors, nurses and patients, as well. In this paper, we tackle this type of dynamic scheduling problem with minimal perturbation by using and comparing two types of approaches: A Segmentation-based heuristic and a Genetic-Algorithm-based schema. The GA-based model which includes homogenous population (GA-HPop) obtains the best performance when tested with a set of real instances. It gets the best characteristics of Genetic Algorithm and adding changes, ensuring a new solution as possible close to original solution.
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Perez-Lopez, A., Baltazar, R., Carpio, M., Terashima-Marin, H., Magaña-Lozano, D.J., Puga, H. (2013). Homogeneous Population Solving the Minimal Perturbation Problem in Dynamic Scheduling of Surgeries. In: Castro, F., Gelbukh, A., González, M. (eds) Advances in Artificial Intelligence and Its Applications. MICAI 2013. Lecture Notes in Computer Science(), vol 8265. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45114-0_37
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DOI: https://doi.org/10.1007/978-3-642-45114-0_37
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