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Accelerated bender’s decomposition algorithm and hybrid heuristics for multi-period planning of maternal healthcare facilities in India

Lookup NU author(s): Dr Ajinkya TanksaleORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Abstract

This work addresses the challenge of improving availability and accessibility of maternal healthcare in India by presenting a multi-period planning problem of hierarchical and successively inclusive healthcare facilities. The problem is formulated as a mixed-integer linear programming model to minimize the overall cost, including the cost of establishing and upgrading the facilities, the cost of allocating/referring the mothers-to-be to the respective facilities and the penalty cost of demotivating the overburdening of the facilities in each time period. To solve the model effectively and efficiently, a Bender's Decomposition Algorithm (BDA) with several acceleration strategies such as valid inequalities, disaggregated Benders cuts, rolling horizon heuristic and parallelism is developed. A Bender's type heuristic is also tested by solving the master problem heuristically. Additionally, a Fix-and-Optimize (F&O) heuristic hybridized with Simulated Annealing (SA) enhanced by various search space reduction techniques is developed to obtain good quality solutions in a reasonable time for large instances. It is evident from the results of the computational experiments that the accelerated BDA and Bender type heuristic outperforms Gurobi. The hybrid F&O and SA is observed to be the most computationally efficient approach. A representative scenario in the Indian setting presents further evidence of the model's applicability.

Publication metadata

Author(s): Chouksey A, Agrawal AK, Tanksale A

Publication type: Article

Publication status: Published

Journal: Journal of the Operational Research Society

Year: 2025

Volume: 76

Issue: 7

Pages: 1299-1318

Online publication date: 29/11/2024

Acceptance date: 15/11/2024

Date deposited: 29/11/2024

ISSN (print): 0160-5682

ISSN (electronic): 1476-9360

Publisher: Taylor & Francis

URL: https://doi.org/10.1080/01605682.2024.2431980

DOI: 10.1080/01605682.2024.2431980

ePrints DOI: 10.57711/45q9-v813

Data Access Statement: Supplemental material available at: https://www.tandfonline.com/doi/full/10.1080/01605682.2024.2431980#supplemental-material-section

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