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Rebounding From Disruptive Events: Optimization of Post-Disaster Reconstruction Activities for Critical and Interdependent Infrastructure Networks
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2020-12-12
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Edition:Final Report
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Abstract:In the aftermath of disasters, when reliable transportation systems are vital, the chaotic and complex environment creates multiple uncertainties and risks in the reconstruction of transportation infrastructures. Damaged transport infrastructures decrease the timeliness of emergency responses and recovery procedures and make it difficult for authorities, who are under excessive pressure and are struggling to find the financial resources to reconstruct them on time and within budget. The aim of this research was to predict the cost performance, schedule performance and cost of reworks in post-disaster reconstruction of transport infrastructures. Significant factors that contribute to cost overruns, schedule delays, and the cost of reworks in post-disaster reconstruction of transportation infrastructures (PRT) were statistically determined in this research. The results demonstrated that 26, 23, and 25 PRTs were statistically significant for cost escalations, schedule delays, and reworks of the mentioned projects, respectively. Three models were developed to predict the cost performance, schedule performance, and cost of reworks, and a stepwise multiple regression method was adopted. The results revealed that seven, nine, and ten PRTs were significant predictors of cost performance, schedule performance, and cost of reworks, respectively. The extreme bound analysis (EBA) method was adopted to determine how robustly each predictor was connected to the corresponding developed model. This project provides accurate knowledge and information that will be helpful in effectively allocating limited resources after disasters and mitigating schedule delays, cost overruns, and reworks in the reconstruction of transportation infrastructures.
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[PDF-4.77 MB]
