A Hybrid Brain Storm Optimization Algorithm to Solve the Emergency Relief Routing Model

Due to the inappropriate or untimely distribution of post-disaster goods, many regions did not receive timely and efficient relief for infected people in coronavirus disease outbreak that began 2019. This study develops a model emergency routing problem (ERRP) distribute more reasonably. Unlike general route optimizations, patients’ suffering is taken into account model, allowing patients urgent situations operations first. A new metaheuristic algorithm, hybrid brain storm optimization (HBSO) proposed deal with model. The algorithm adds ideas simulated annealing (SA) large neighborhood search (LNS) BSO improving its ability escape from local optimum trap speeding up convergence. In simulation experiments, BSO+LNS (combining LNS), HBSO LNS SA) are compared. results experiments show following: (1) outperforms rivals, obtaining smaller total cost providing stable discover best solution ERRP; (2) ERRP can greatly reduce level patient prioritize situations.