Research On The Optimal Scheduling Of Emergency Maintenance Tasks Oriented To Combat Missions

In the modern high-tech battlefield environment,the equipment has high damage rate and complex failure modes.Timely and effective battlefield maintenance can quickly restore combat effectiveness,which is an important means to win.Scientific and reasonable task scheduling can not only effectively improve the efficiency of maintenance,but also reduce the cost and achieve precise maintenance.To further improve the combat effectiveness of the troops,this paper proposes a mission-oriented optimal scheduling method for battlefield maintenance,to optimize the scheduling of the maintenance tasks of the mobile repair units.The method takes the sum of the loss of the importance of the combat unit as the optimization goal,and uses the improved genetic algorithm to optimize.Firstly,the importance of each equipment in the combat unit is evaluated.Then,the improved genetic algorithm is used to optimize the allocation of maintenance tasks considering the residual life.The main innovations of this paper are reflected in the following aspects:1.From the perspective of equipment support,the equipment importance evaluation method is studied.In order to ensure the completion of combat missions,it is necessary to put the key equipment first and give consideration to the general in the maintenance process.According to the basic principles of emergency maintenance command,an indicator system is established to evaluate the importance of equipment from the command and control relationship,combat capability and combat space.The complex network theory,the judgment matrix method and the expert scoring method are used to evaluate the importance of the indicators,and the evidence fusion theory is used to integrate the importance of the indicators,which effectively improves the objectivity of the evaluation result and provides a decision basis for the optimal scheduling of maintenance tasks.2.In order to solve the problem that the battlefield information is not fully utilized in the maintenance mode of post-failure,this paper proposes an optimization scheduling method for the maintenance task considering the residual life.The battlefield maintenance mode is analyzed and researched,and the optimal scheduling model considering the residual life is established.And the problem is optimized by using improved genetic algorithm under the multi-dimensional and complex constraints of equipment residual life,equipment importance,spare part resource availability,combat mission time constraints and so on.Compared with the traditional mode of maintenance after failure,this method takes the usable equipment into consideration,and by adequate consideration,it can effectively reduce the loss of importance of the combat unit.3.To solve the problem that the existing optimization algorithm has poor optimization effect in this problem,the genetic algorithm is researched and improved,and the genetic algorithm of adjacent two gene crossover operators is designed.The crossover operator crosses in the goal of obtaining as many excellent gene fragments as possible for the offspring,which improves the continuous evolution ability of the population and provides support for task optimization scheduling.4.Finally,on the basis of the theoretical research,a prototype system for battlefield maintenance task scheduling is designed and verified by an example.The results of the example show that the equipment importance evaluation method based on multi-indicator fusion is stable and reliable.The task scheduling considering the residual life can reasonably allocate the tasks between groups,make full use of the residual life,and effectively reduce the equipment importance loss.The prototype system is simple and easy to use.The rationality and effectiveness of the method are verified.