Abstract
After a natural disaster or a large-scale incident, some of the utility lines and essential roads around the damaged centers may be blocked by debris from the disaster. This incident can immediately restrict crucial supply distribution and affect rescue plans. Therefore, the recovery of damaged roads is an essential step to help increase the effectiveness of the relief operations and to reduce victims’ suffering. In this study, we develop a mixed-integer programming model for optimal scheduling and routing of repair crew and relief vehicles after the disaster. The objective function is to minimize the total relief time of the disaster-affected nodes and the recovery time of damaged nodes. Demand nodes are manually weighed according to a presumed degree of damage. Given the NP-hardness nature of the problem, a hybrid approach is proposed based on the Benders decomposition method and a heuristic algorithm. The heuristic algorithm is employed as an initiation algorithm to generate an initial solution for the Benders decomposition algorithm. The routing of the repair crew and relief vehicles is drawn using the Benders decomposition algorithm. To demonstrate the performance of the hybrid algorithm, an ant colony optimization algorithm is also developed. The computational results demonstrate that the proposed approach is capable of computing a near-optimal solution in less CPU time. Furthermore, the performance of this hybrid approach is distinctively superior when it comes to routing of medium to large-scale problems.
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Lakzaei, S., Rahmani, D., Tosarkani, B.M. et al. Integrated optimal scheduling and routing of repair crew and relief vehicles after disaster: a novel hybrid solution approach. Ann Oper Res 328, 1495–1522 (2023). https://doi.org/10.1007/s10479-023-05397-0
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DOI: https://doi.org/10.1007/s10479-023-05397-0