Multi-objective mammography unit location–allocation problem: A case study

This work addresses the Multi-Objective Mammography Unit Location–allocation Problem (MOMULAP), aiming to meet three objectives: maximize mammography screening coverage, minimize the total distance traveled weighted by the number of users, and maximize equity in access to mammography screening. We i...

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Bibliographic Details
Published in:Operations research for health care 2024-06, Vol.41, p.100430, Article 100430
Main Authors: de Campos, Marcos Vinícius Andrade, de Assis, Romário dos Santos Lopes, Souza, Marcone Jamilson Freitas, de Siqueira, Eduardo Camargo, Silva, Maria Amélia Lopes, de Souza, Sérgio Ricardo
Format: Article
Language:English
Subjects:
Facility location
Location–allocation problem
Mammography screening
Multi-objective optimization
NSGA-II
SPEA2
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Summary:This work addresses the Multi-Objective Mammography Unit Location–allocation Problem (MOMULAP), aiming to meet three objectives: maximize mammography screening coverage, minimize the total distance traveled weighted by the number of users, and maximize equity in access to mammography screening. We introduce a mixed-integer nonlinear programming (MINLP) formulation to represent the MOMULAP and algorithms based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Strength Pareto Evolutionary Algorithm (SPEA2) for treating it. The algorithms were tested with data from seven Brazilian states. In these states, the number of cities ranges from 139 to 853, equipment from 23 to 347 units, and estimated annual demand for screenings from 96,592 to 1,739,085. The solutions provided by this work allow health managers to choose the appropriate location and allocation of the mammography units, considering different objectives.
ISSN:2211-6923
2211-6931
DOI:10.1016/j.orhc.2024.100430