Network optimization problem applicable for breast cancer screening cost minimization
Abstract
We investigate the problem of breast cancer screening optimization, using various techniques applicable in domains where the data format is not defined in advance. The aim is to minimize the cost related to the screening of patients while maximizing the beneficial effect of the process regarding some key breast cancer indices. Our model can be easily adjusted to other similar network optimization tasks where a goal function has to be minimized across a geographical surface. We present the problem’s key similarities to the Travelling Salesman Problem and underline the fact why we choose a deterministic algorithm compared to a Simulated Annealing-based solution. Furthermore, we present the usefulness of the Elastic Stack regarding this application and offer a concrete solution to the problem defined by our generated dataset, respecting the European data distributions in this domain.
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