Uncertain demand estimation with optimization of time and cost using Facebook disaster map in emergency relief operation

When a disaster disrupts a society within a moment without a little warning, the living people of those areas face the deprivation due to demolition. Facebook, one of the most popular social media plays a vital role in response to the victims. The authority of Facebook has launched safety check feature to know about the requirement after the disruption of disaster and based on the information, a intensity factor is defined for requirement of relief products in this research work. Estimating the amount of relief products through intensity measure, our research work has introduced a mathematical model for initiation of humanitarian logistic operation plan. The research has focused on two objective functions through the mathematical model which are minimization of total cost and response time. The model with two objective functions is converted to a equivalent compromise model with neutrosophic compromise programming approach. Deterministic and non-deterministic both algorithms are implemented in the solution process of the compromise mathematical model. In deterministic approach, mathematical model is varified with different methods to obtain compromise results. For non-deterministic approach, a genetic algorithm is proposed to solve the model. The model is experienced with a numerical example and hereby statistical investigation is performed considering different dimension varying the parameters of the model. (C) 2019 Elsevier B.V. All rights reserved.