An automated model for optimizing budget allocation in earthquake mitigation scenarios

Motamed, Hooman; Khazai, Bijan; Ghafory‐Ashtiany, Mohsen; Hosseini, Kambod Amini

doi:10.1007/s11069-011-0035-y

Cited by 22 publications

(5 citation statements)

References 7 publications

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“…Such perspectives led to the formation of a very different modeling framework with a format that is much closer to regional loss estimation methodologies. Others contributing to these categories of modeling include Dodo et al, (3,9) Davidson et al, (2) Xu et al, (10) Vaziri et al, (7) Legg et al, (11) and Motamed et al (12) All these models (except Legg et al (11) ) presented their work for earthquake risk mitigation decisions for part of a city or a region. In almost all these models, linear programs were developed to formulate regional earthquake risk mitigation resource allocation to perform for a pilot area.…”

Section: Models For Finding Optimal Risk Mitigation Measuresmentioning

confidence: 99%

Implementation of Equity in Resource Allocation for Regional Earthquake Risk Mitigation Using Two‐Stage Stochastic Programming

Zolfaghari

Peyghaleh

2015

Risk Analysis

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This article presents a new methodology to implement the concept of equity in regional earthquake risk mitigation programs using an optimization framework. It presents a framework that could be used by decisionmakers (government and authorities) to structure budget allocation strategy toward different seismic risk mitigation measures, i.e., structural retrofitting for different building structural types in different locations and planning horizons. A two-stage stochastic model is developed here to seek optimal mitigation measures based on minimizing mitigation expenditures, reconstruction expenditures, and especially large losses in highly seismically active countries. To consider fairness in the distribution of financial resources among different groups of people, the equity concept is incorporated using constraints in model formulation. These constraints limit inequity to the user-defined level to achieve the equity-efficiency tradeoff in the decision-making process. To present practical application of the proposed model, it is applied to a pilot area in Tehran, the capital city of Iran. Building stocks, structural vulnerability functions, and regional seismic hazard characteristics are incorporated to compile a probabilistic seismic risk model for the pilot area. Results illustrate the variation of mitigation expenditures by location and structural type for buildings. These expenditures are sensitive to the amount of available budget and equity consideration for the constant risk aversion. Most significantly, equity is more easily achieved if the budget is unlimited. Conversely, increasing equity where the budget is limited decreases the efficiency. The risk-return tradeoff, equity-reconstruction expenditures tradeoff, and variation of per-capita expected earthquake loss in different income classes are also presented.

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Section: Models For Finding Optimal Risk Mitigation Measuresmentioning

confidence: 99%

Implementation of Equity in Resource Allocation for Regional Earthquake Risk Mitigation Using Two‐Stage Stochastic Programming

Zolfaghari

Peyghaleh

2015

Risk Analysis

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“…Results indicate that Mc is equal to 4.7, 4.5, and 4 for the 1900-1963, 1963-2000, and 2000-2022 time spans, respectively. By completing the event catalog, the seismicity parameters were calculated considering methods suggested by Gutenberg-Richter and Kijko for all seismic zones (Gutenberg, B.; Richter 1944), [42].…”

Section: Hazardmentioning

confidence: 99%

A Risk-Based Model for Allocating Post-Earthquake Reconstruction Finance in Medium-Size Iranian Cities

Kazemiasl,

Motamed,

Fazlavi

2024

Preprint

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This research proposes efficient financial resource allocation methods in post-earthquake urban reconstruction. Considering the economic challenges associated with such projects, having a predefined plan to identify and address gaps and challenges is crucial. The study emphasises the significance of conducting pre-disaster studies to manage post-disaster financial resources better. Metropolitan Tehran, particularly District 2 of Tehran municipality, was chosen as a case study due to its high importance, vulnerability, and risk. The research encompasses two main parts: seismic risk assessment and allocating financial resources for reconstruction. The first part employed risk analysis and computer programming for seismic risk modelling. In the second part, allocation methods for post-disaster budgets were proposed through interviews, past experiences, and computer programming. Various scenarios were considered for financial resource allocation, and an algorithm was developed to evaluate the reconstruction progress rate over time. The results indicate that, for optimistic, probable, and pessimistic scenarios, the post-earthquake reconstruction process for an urban area with characteristics similar to District 2 of Tehran municipality is estimated to conclude, on average, in 4.3, 9.2, and 11.3 years, respectively. This research provides valuable insights into effective resource allocation strategies, emphasising the importance of pre-disaster planning for efficient post-disaster reconstruction.

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“…Fwa and Farhan (2012) propose a two-stage method to solve a dual-level multi-asset, multi-objective optimal budget allocation problem for pavement network maintenance. Motamed et al (2014) present a budget allocation model for earthquake mitigation scenarios. The proposed automated model quantifies earthquake losses and evaluates the cost-effectiveness of each scenario.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal Budget Allocation to Improve Critical Infrastructure during Earthquakes

Edrisi

Askari

2020

Transp. j.

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This article studies the integrated role of three infrastructure management agencies with responsibilities that span from pre-disaster mitigation and preparedness actions to post-disaster response operations during earthquakes. Each agency's actions are constrained by a given budget that is assigned to that agency by a master decision-maker (the federal government). This article presents a bi-level Stackelberg game where the master decision-maker allocates a total budget between the agencies with the objective of minimizing the earthquake death toll. A meta-heuristic particle swarm optimization algorithm is used to find the optimal solution of the Stackelberg game. Results show that in lower budgets, it is better to invest in the emergency response agency and the transportation agency. Furthermore, the results indicate that excessive investment in the transportation agency without adequate investment in the emergency response agency is inefficient.

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An automated model for optimizing budget allocation in earthquake mitigation scenarios

Cited by 22 publications

References 7 publications

Implementation of Equity in Resource Allocation for Regional Earthquake Risk Mitigation Using Two‐Stage Stochastic Programming

Implementation of Equity in Resource Allocation for Regional Earthquake Risk Mitigation Using Two‐Stage Stochastic Programming

A Risk-Based Model for Allocating Post-Earthquake Reconstruction Finance in Medium-Size Iranian Cities

Optimal Budget Allocation to Improve Critical Infrastructure during Earthquakes

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