Abstract
Medical and fire resources are scheduled to chemical industrial parks which have caused mass casualties due to accidents. However, most of models of emergency logistics do not account for pre-rescue before large-scale rescue which may increase the casualty rate because of the long emergency response time and distance. This paper presents a mathematical model proposed for optimal distribution of emergency resources for rescuing the trapped victims who are highly likely to be seriously injured or even killed before the arrival of ambulances and fire engines. Due to the different types and risks of accidents at various locations have different impacts on people, we consider the detailed characteristics of accident scenarios and maximum tolerance time for the trapped victims to determine the priority of rescue sites. In addition, this paper proposes two indices of pavement resistance coefficient and obstacle to reflect the environment after accidents, which are not involved in other models of emergency resources distribution. Based on these, a penalty cost objective function is established to maximize the rescue rate. The optimal delivery route which reflects the distribution process is planned for the robot that will save more casualties. Two simulations and a real accident case study were conducted by minimizing the objective function, and the numerical results showed the reliability and effectiveness of the presented model for making optimal decisions for emergency distribution to accidents in chemical industrial parks.
Published Version
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