MODELING THE DISTRIBUTION OF MAMMOGRAPHY SCREENINGS USING A MULTI-OBJECTIVE APPROACH

Premature detection of breast cancer is essential to reduce the number of deaths. However, this detection is depending of the adequate location and allocation of mammography equipment in order to supply the demand of women who need perform the exam. In this sense, this work presents a multi-objective programming approach to model the problem of locating and allocating mammography units, maximizing the demand coverage and minimizing the distance traveled by women to access the mammography exam. Exact resolution methods are studied and implemented to capture and analyze the Pareto frontier: the weighted sum, epsilon-restricted, and goal programming, employing different variations. The results show that these methods offer satisfactory solutions to be applied to the problem and are able to determine a dispersed Pareto frontier, allowing the validation of the conflict between the objectives.