From Pallets to Puppies: Using Insights from Logistics to Save Animals

Abstract

The Kentucky Humane Society (KHS) is a private, nonprofit organization dedicated to saving every healthy, behaviorally sound animal that they take in. They are also the largest no-kill animal shelter in Kentucky, USA. Due to limited resources, the KHS has a great need for an optimized methodology for allocating available animals to their adoption facilities. Workers at the KHS believe that a capacity constraint is their most limiting factor. The purpose of this work is to develop an allocation model that will improve the throughput rate of the animals to be adopted, thereby freeing up extra capacity more quickly than current practices. The allocation model presented here assigns animals to adoption locations based on their expected length of stay at all available locations. The resulting allocation minimizes the expected length of stay for these animals. In order to make the model easy to use, we have implemented a software with a user-friendly interface.