open access

https://hdl.handle.net/2115/100439

Search Path Optimization Method Considering Building-Specific Probability of Victims Requiring Rescue and Time Dependent Decay of Survival Rates

英語

Extended Traveling Salesman Problem (TSP)

2026-07-01

Proceedings of the 10th International Symposium on Reliability Engineering and Risk Management (ISRERM 2026)

This study proposes a search path optimization method for post-earthquake rescue operations that considers both the spatial distribution of people requiring rescue and the time-dependent decline in survival rate. Conventional search planning often prioritizes the shortest travel distance, although such a route does not necessarily maximize the number of people rescued when damage is unevenly distributed. In this study, building-specific seismic motion is estimated first, and the expected number of people requiring rescue is calculated from building damage probability and occupancy information. For practical search operations, these values are aggregated at the block level, and a rescue score is defined by combining the expected number of people requiring rescue with the survival rate at the arrival time. Monte Carlo simulations were carried out for a virtual city consisting of eight districts while keeping the total expected number of people requiring rescue constant at 40. The results showed that the score-maximizing route increased the average expected number of rescues by 4.9 and improved the rescue rate from about 35% to 47% compared with the shortest path. These results demonstrate the effectiveness of incorporating victim distribution and survival-rate decay into rescue route planning.

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