Theory Research Of Optimal Scheduling And System Development Of Auxiliary Decision-making About Oilfield Operating Special Vehicle

In the operating production process of oilfield,equipment or material need to be transported by special vehicles for the normal production of operation team timely,and the scheduling process of special vehicles needs the unit cooperation of special vehicle group and so on based on the human experience.Since the number of tasks is much more than special vehicles,the scheduling process is complexed and the human experience is limited,the scheduling process always result in operation tasks have no special vehicle to be serviced,the used number of special vehicles is too much,and the driving distance of special vehicles is too long.Therefore,in order to improve the special vehicles utilization,and complicate the operation tasks,and avoid the operation accidents,and achieve the goal of increasing the operation efficiency,the research of special vehicles static and dynamic optimization scheduling have been proposed,and the auxiliary decision system of special vehicles optimization scheduling has been designed in this paper.For the task,which demand information is confirmed and tasks need special vehicles to service in tomorrow.In order to improve the utilization rate of vehicles and increase the number of tasks completed,a multi-objective and multi-priority optimization method has been proposed in this paper.The minimum number of vehicles have been taken as the main target,and the maximum number of tasks have been taken as the secondary target,and the shortest driving distance have been taken as the thirdly target,and the constraint conditions have been analyzed in this method.First of all,considering the minimum number of vehicles,the improved K-means algorithm and the shortest distance method have been adopted to optimize grouping according to the type of different task.Secondly,considering the maximum number of tasks,the improved genetic algorithm has been adopted to optimize the selection for the task group.Finally,considering the shortest driving distance,the exhaustive method has been adopted to optimize the path of driving.For the task,which happen in the production process and need to be done timely.In order to deal with the task more timer and make the result of vehicle scheduling much better,a local optimization scheduling method has been proposed in this paper.First,the characteristics of real-time demand information have been analyzed,and then,the maximum number of tasks completed has been taken as the dynamic scheduling optimization objective.In this method,in order to complete much more tasks by working special vehicles,the dynamic insertion method by the way has been used to deal with the small number of the accident,and the improved genetic algorithm has been used to deal with the much number of the accident.In order to achieve the application of special vehicles optimization scheduling and provide a kind of auxiliary decision-making method for scheduling,an auxiliary decision system of special vehicles optimization scheduling has been designed and inserted into the operation management platform.The traditional scheduling plan and the scheduling plan could be formulated by the human experience and the corresponding optimization method,and.For providing an auxiliary decision-making advice,the contrast result of index parameters between artificial scheduling and optimal scheduling could be formulated automatically.At last,the best scheduling plan could be selected by the advice of aid decision making.Through the simulation experiment,the feasibility and effectiveness of the proposed method and the designed system have been indicated.