Robustifying humanitarian relief systems against travel time uncertainty

Abstract

We consider a class of last mile distribution problems with multicenters and multiareas in disaster management, where the travel time for every pair of center‐area is uncertain. We propose a chance‐constrained model to handle this problem, which simultaneously determines the selection of emergency logistics centers (ELCs), the amount of relief transported to these ELCs, the allocation and routing of vehicles, and the equitable distribution of emergency materials from the ELCs to the disaster areas. We develop a distributionally robust optimization (DRO) model to reformulate the chance‐constraint model as a second‐order cone programming, which the proposed algorithm can solve efficiently. We present a case study of the Yushu earthquake in the Qinghai Province of the People's Republic of China to demonstrate the performance of our proposed model and method. The results reveal that (1) the DRO method outperforms the scenario‐based model in reducing cost and improving reliability, (2) deploying a large number of vehicles in the emergency centers near disaster areas can reduce cost, and (3) our proposed model evenly distributes vehicles on paths to curtail the rescue time.

Multi-Level Site Selection of Mobile Emergency Logistics Considering Safety Stocks

“…Calculation Step 6: Immunization operation-immunize the antibody population, i.e., selection, crossover, and mutation, according to the results of Step 3. The roulette mechanism performs selection [20,21] using the expected reproduction probability obtained from (10) as the individual selection probability. The crossover was operated by the single-point crossover method.…”

“…To justify the efficiency of the method, the article proposed a trust-region-based decomposition method to solve the RTSPM. To respond to the emergency relief problem of uncertainty in the last-mile delivery time, Zhang [10] proposed an opportunity constraint model. This model considers emergency fair siting as emergency logistics centers (ELCs).…”