A biobjective hierarchical location-allocation approach for the regionalization of maternal-neonatal care

Karakaya S., Meral S.

SOCIO-ECONOMIC PLANNING SCIENCES, vol.79, 2022 (SCI-Expanded) identifier identifier

  • Publication Type: Article / Article
  • Volume: 79
  • Publication Date: 2022
  • Doi Number: 10.1016/j.seps.2021.101093
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, Academic Search Premier, International Bibliography of Social Sciences, Business Source Elite, Business Source Premier, EconLit, Educational research abstracts (ERA), Geobase, INSPEC, Political Science Complete, Public Affairs Index, Social services abstracts, Sociological abstracts, Worldwide Political Science Abstracts
  • Keywords: Maternal-neonatal, Health care, Hierarchical location-allocation, p-median, Top-down heuristic, Lagrangean relaxation, PERINATAL FACILITIES, SERVICE NETWORKS, MODEL, DECOMPOSITION, MUNICIPALITY, HOSPITALS, DESIGN
  • Middle East Technical University Affiliated: Yes


This study proposes a biobjective location-allocation model for the regionalization of maternal-neonatal care to increase both accessibility and cost-efficiency by minimizing total transportation costs to public in accessing services and total service costs to government simultaneously. The model is characterized by a three-level successively inclusive hierarchy with an integrated flow and bidirectional referrals. Since it is difficult to solve for the optimum in a reasonable time, three heuristics are developed: top-down heuristic, novel top-down heuristic, and Lagrangean relaxation. A significant result obtained from the computational study is that at least one of the heuristics provides high-quality solutions in reasonable computational time for any level of the policy variable in weighting the two objectives. To demonstrate its practicality, the proposed hierarchical locationallocation model is applied to a case study based on the southeastern Anatolian region of Turkey.