Research On LNG Road Tanker Scheduling Optimization With Stochastic Demand

Liquefied Natrual Gas is referred to LNG.In recent years,clean and efficient resources has become increaisng popular.People has attach great importance to LNG for its advantages,and it has been applied in various industries.Subsquently,the way of transportation for LNG has become a major problem since its risks.China's railway transportation of LNG has not opened,so most LNG enterprises use flexible tanker to finish work.The rapid development of LNG tanker transportation has put higher requirements for us to make safe plan.LNG tanker dispatching plan should take safety and cost of transportation into consideration.LNG tanker transportation is the continuation and development of pipelines and maritime on land,and is the bridge between dispatching center and filling stations.Nowadays,many LNG enterprises still use the experience method when formulating the vehicle dispatching plan.The transportation cost of this method is high and the risk of tanker transportation can not be understood.Once the accident occurs,we can not rescue timely.Reduce the company's service quality.LNG tanker scheduling is related to many factors,the situation is complex.In the process of tanker scheduling,there are uncertain factors such as random demand,random customer location,random service time and random driving time of the vehicle.So based previous research on LNG vehicle scheduling problem,this paper analyzes the characteristics of LNG,the influencing factors of LNG tanker transportation and the vehicle scheduling problem under different conditions.Taking the transportation risk and the transportation cost as objectives,a mathematical model of multi-objective opportunity constrained programming with time window is established,the uncertainty of customer's demand and driving time of tanker on the road are considered in the model.According to the characteristics of LNG,the model constraints are limited to make the model more realistic.The problem of LNG tanker scheduling under stochastic demand is solved by the combination of stochastic simulation technology and genetic algorithm,and the feasibility of the algorithm is verified.