# Scenario-Based Emergency Material Scheduling Using V2X Communications
## 2 Literature Review  
Various programming models have been developed for emergency logistics, including linear programming, integer or mixed integer programming, and mixed integer linear programming [7; 8]. [PERSON] et al. [9] employed a classification-based method to identify cost functions and constraints for primary emergency operations in relief distribution. [PERSON] et al. [10] addressed the reliable humanitarian response planning for a fleet of vehicles and proposed a genetic algorithm. [PERSON] et al. [11] built a compromise programming model for multi-criteria optimization in last-mile humanitarian distribution. The model is able to produce an actual vehicle schedule while forcing vehicles to form convoys in humanitarian operation research. [PERSON] et al. [12] proposed a multi-warehouse location-route model considering network failures, multiple vehicle use and standard rescue time, which could significantly reduce scheduling time at the expense of more local warehouses and vehicles. [PERSON] et al. [13] evaluated the performance of relief logistics in a disaster in Ghana with emphasis on the coordination of emergency relief operation and effectiveness of inventory management. [PERSON] et al. [14] proposed a multi-objective robust possibilistic programming model, which simultaneously considered maximizing the distributive justice in emergency material scheduling, minimizing the risk of relief distribution, and minimizing the total logistics costs. Many researchers took into account uncertainty in relief distribution and developed stochastic programming models or robust optimization models [15; 16]. [PERSON] et al. [17] proposed a multi-objective stochastic model to manage the logistics in earthquakes. [PERSON] et al. [18] used the triangular fuzzy number to describe the emergency demands and introduced the time-dependent function to simulate the dynamic road network. [PERSON] et al. [19] presented a Petri net-based method E-Net for an emergency response process constrained by resources and uncertain duration. [PERSON] et al. [20] developed a multi-objective robust stochastic programming approach for the emergency material scheduling under uncertainty. Not only demands but also supplies and the cost of procurement and transportation were considered as the uncertain parameters. For emergency material scheduling, it is an important indicator to improve the overall demand satisfaction of the disaster areas and guarantee the fairness simultaneously. In recent years, fairness has been widely studied. According to [21], the Theil L index is sensitive to low income. Emergency material scheduling (EMS) cannot ignore the disaster areas with low demands, so we chose the Theil L index to indicate the fairness of material scheduling. [PERSON] et al. [22] took the satisfaction of the whole disaster areas as the objective and built a model for multi-commodity, multi-supply depot, multi-disaster depot, and multi-mode of transportation, so as to maximize the rescue efficiency of EMS. [PERSON] et al. [23] applied two basic round-robin-based greedy search algorithms and proposed an optimized algorithm for fair delivery of relief supplies. [PERSON] et al. [24] dynamically adjusted the distribution schedules from various supply depots according to the requirements at demand depots to minimize unsatisfied demand for resources, time for delivery, and transportation costs. However, they researched fairness from the perspective of demand satisfaction and ignored the impacts of different disaster scenarios on the fairness of material scheduling. Thus, we tried to combine the urgency of a disaster scenario and traditional fairness to construct a more reasonable optimization objective with the help of V2X communications. For V2X communications, some issues, including cyber security and standardization, were discussed in [25]. A framework for real-time video processing is proposed with the design of object detection algorithms in [PERSON] et al. [27]. [PERSON] et al.