A new hierarchical facility location model and genetic algorithm for humanitarian relief

A responsive and effective humanitarian relief is needed when the disaster happens suddenly. However, there are many sophisticated reasons prevent the coordination with other relief organizations and then decrease the responsibility and efficiency of relief. Thus a hybrid facility location model with non-fixed levels, shortest-longest radiuses, limited capacities, least warehouses and hubs, and uneven hierarchies with new discount factor a and global X. reduction is developed. Better to support the humanitarian relief, higher the cost and more complex of the relief network will usually be. It implies the production and conservation of feasible solutions more difficult when genetic algorithms are applied. Therefore, we propose the loci swap and adaptive contest for multi-fitness functions to improve the genetic algorithm. The experimental results show the utility and practicability of the developed hierarchical network model and corresponding solution genetic algorithm.