Solution of a single-objective based three-stage 4DTP model with information crowdsourcing under disaster relief scenario: a hybrid random type-2 fuzzy approach

In the event of any type of disaster or emergency, quick action is required to save lives, meet the basic human needs of the affected population, and reduce the amount of damage. In this situation, national organizations, local organizations, or international organizations should participate in providing assistance as soon as possible. However, priority should be given to local agencies in providing assistance as they are more familiar with the geographical location of the affected areas. Effective coordination efforts are most beneficial and important in disaster relief. Again, certain local organizations have high demand but limited resources. In this situation, organizations have great difficulty in optimally allocating resources. The problematic fact is addressed in this essay by proposing the idea of demands-based priority measures. A mechanism is introduced to determine the priority factor’s numerical value by employing information crowdsourcing to gather responses regarding the need for relief supplies. In this context, under the hybrid random type-2 fuzzy environment a three-stage 4DTP model is developed where the local organizations fulfill the demand with the highest priority in Stage-I, the other international or national organizations fulfill the remaining demand in Stage-II, and local organizations are restored in Stage-III. In our proposed model, all constraints and all objective functions are de-randomized by the probability chance constraint technique and expected value method respectively. Then, using CV-based reduction method the proposed optimization models is de-fuzzified and finally, using GRG method via Lingo $$-$$ - 18.0 software, these modified crisp models are solved. Some real-life information is illustrated by providing numerical examples of the proposed approach - which shows how a decision maker controls minimum cost.