Supporting Efficient Assignment of Medical Resources in Cancer Treatments with Simulation-Optimization

When scheduling multi-period medical treatments for patients with cancer, medical committees have to consider a large amount of data, variables, sanitary and budget constraints, as well as probabilistic elements. In many hospitals worldwide, medical specialists regularly decide the optimal schedule of treatments to be assigned to patients by considering multiple periods and the number of available resources. Hence, decisions have to be made upon the priority of each patient, available treatments, their expected effects, the proper order and intensity in which they should be applied. Consequently, medical experts have to assess many possible combinations and, eventually, choose the one that maximizes the survival chances or expected life quality of patients. To support this complex decision-making process, this paper introduces a novel methodology that combines a biased-randomized heuristic with simulation, to return 'elite' alternatives to experts. A simplified yet illustrative case study shows the main concepts and potential of the proposed approach.