Optimization Model And Algorithm Design Of Dynamic Distribution Of Emergency Materials Under Evolving Demand

In recent years,emergencies have occurred frequently,seriously affecting economic development and social stability.In order to rescue people’s lives and property in time and reduce losses caused by disasters,emergency materials must be dispatched to the emergency logistics center in time and quickly,and then distributed to the disaster-affected areas.Since emergencies are characterized by uncertainty,it is of great significance to scientifically predict the actual needs generated by disaster sites to improve rescue efficiency.Based on the research results in relevant fields at home and abroad,this paper adopts literature research method,combination of qualitative and quantitative analysis,mathematical modeling method,numerical experiment method and other research methods.In this paper,the dynamic distribution of emergency materials under the situation of evolving demand is explored in depth.Firstly,In view of the shortage of emergency supplies during natural disaster rescue,a dynamic optimization model for emergency supply dispatching and distribution is formulated in this paper.Due to the fact that the state of the emergency demand usually changes with the evolution of unexpected disaster,the markov decision processes(MDP)is used to predict the demand tendency of each victim group in each decision-making period.In the model,the impact of material supply strategy on the self interests of each disaster affected point under the condition of insufficient supply is comprehensively considered,and a deprivation cost function is used to measure the loss of the victims when they keep waiting for the arrival of emergency supplies,and the optimization framework is to minimize the total cost of both deprivation cost and emergency operational cost.In Python programming platform,PULP is called to solve the material allocation strategy in each decision-making period..The numerical results with different scales of road networks show that the embedded heuristic algorithm performs efficiently even for larger network,and The model and algorithm proposed in this paper not only give the specific optimal emergency supply dispatching and distribution strategy in each rescue period,but also take into account the fairness of each victim group under the condition of reducing the total system cost as much as possible,which is obviously beneficial for providing effective decision support.In addition,in view of the shortcomings of the traditional vertical transport mode,considering that emergency supplies ordered from the central distribution center before the occurrence of demand may lead to the shortage of emergency supplies in some disaster points and redundancy of emergency supplies in other disaster points,in order to make full use of emergency supplies and improve rescue efficiency,the horizontal inventory allocation strategy of emergency supplies between disaster points is adopted.According to the material consumption of the victims after the emergency,multi-cycle scheduling should be carried out to guarantee the materials of the victims in each demand cycle,and then the dynamic optimization model of emergency material allocation can be established.In the model,the interests of three parties,including material redundancy point,material scarcity point and decision-makers,are comprehensively considered,and multi-party negotiation rules are formulated.The construction of the model objective function and negotiation rules can not only ensure the internal fairness of each subject,but also balance the interests of each subject.An algorithm was designed to solve this problem,and PULP was used to solve the problem in the material allocation strategy of each decision-making period in the Python programming platform.The model and algorithm proposed in this paper can not only provide emergency materials allocation strategies for each period of the golden rescue period,but also play a good role in accelerating material turnover,reducing the total system cost,preventing stock shortage and improving rescue quality.In addition,the constructed transverse transport model is more close to the actual situation and can provide effective decision support for emergency management departments.