Designing humanitarian supply chains by incorporating actual post-disaster decisions

Existing models for disaster preparedness and response address network design and resource allocation challenges. However, these models typically adopt a global optimization point of view, which may not be attainable since they do not consider the actual decision-making process after a disaster occurs. This process is based mostly on practitioners' knowledge and experience, rules of thumb and the population behavior. In this paper, we develop a new mathematical model that incorporates such practical considerations. The model includes actual post-disaster decisions through a set of “humanitarian constraints”. We then present an efficient optimal solution method to solve small/medium-size instances of the resulting problem and a heuristic algorithm based on the Tabu-search method for large instances of the problem. We test our methods on problems with randomly generated data, as well as real data obtained from the Geophysical Institute of Israel. The results demonstrate that our heuristic performs exceptionally well, and optimal solutions are obtained in almost all cases. More importantly, we show that ignoring the actual decision-making process that occurs at the post-disaster stage results in inferior actual overall solutions. Using the humanitarian constraints improves the entire supply chain performance. Therefore, it is critical to accurately incorporate post-disaster decisions during the pre-disaster planning phase.