Optimizing strategies for post-disaster reconstruction of school systems

Irene Alisjahbana, Andrei Graur, Irene Lo and Anne Kiremidjian

Reliability Engineering and System Safety, 2022, vol. 219, issue C

Abstract: School systems are often significantly impacted after disasters, forcing students to transfer to neighboring schools and resulting in worse learning conditions. In this paper, we take an optimization approach to reconstructing schools as soon as possible to improve student well-being. We focus on the scenario in which a central decision-making authority is responsible for the reconstruction of the school system. Limited construction crew availability means that schools must be reconstructed in sequence, and we study the order in which schools should be reconstructed to minimize the time and distance students travel to neighboring schools. We formulate a greedy algorithm through intuitive examples and discuss advantageous properties of this algorithm. We prove that finding the optimal reconstruction order with multiple construction crews is NP-hard, but our greedy algorithm finds a reasonable solution in polynomial time. We then extend the greedy algorithm to a typical post-disaster scenario incorporating school capacities, multiple construction crews, and temporary schools. Finally, we empirically evaluate our greedy policy in a case study using data after the 2018 Lombok Earthquakes and demonstrate that our greedy algorithm performs significantly better than policies typically considered by decision-makers. Our results demonstrate how theoretically motivated policies can be useful for post-disaster decision-making.

Keywords: Disaster recovery; School reconstruction; Optimization; Greedy algorithm (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:219:y:2022:i:c:s0951832021007298

DOI: 10.1016/j.ress.2021.108253

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