Research On Task Path Optimization Algorithm For Housing Defect Management System

In recent years,the house quality and living comfort has become the primary consideration when people in the purchase of housing.According to incomplete statistics,in the survey of real estate business housing customer satisfaction found that the satisfaction of property service was significantly lower than that of housing facilities and real estate enterprise brand trust.At the time of delivering houses,because the more or less defects in the quality of housing,the acceptance of homeowner is not pass,which led to many real estate projects postponement of delivering houses,so that the cost of real estate business development become higher,the reputation become poor and the market competitiveness becomes smaller.Therefore,before delivering the houses,the property company must inspection carefully to the houses which will be delivered.Once any defect in the housing is found,the property company must report it to the construction unit timely and require the construction side to provide maintenance services,this can improve the real estate business brand trust,and market competitiveness.Based on this background,this paper studies the inspection task path optimization problem.In the actual inspection work,due to both the distribution range and the number of rooms are large,each room has different inspection type and inspection deadline window,which has brought great difficulties and inconvenience for the inspection personnel inspection work,therefore planning a reasonable inspection path for the inspection personnel to improve the inspection efficiency and reduce the cost of inspection is very important.The main research work of this paper are as follows:(1)Establish a one-to-many inspection task path optimization model.Analysis the specific inspection task path optimization problem,plan the optimal inspection task route for the inspectors in the next few days,establishing a one-to-many inspection task path optimization model.According to the one-to-many characteristics of the model,optimized the express method of time window and the reach time of the inspection point when patrolled cross days.According to the three-dimensional characteristics of the model,optimized the express method of available distance between any two rooms in three-dimensional space.(2)Based on the model and the distribution characteristics of the inspection point to improve the ant colony algorithm.Combines the inspection path optimization model and ant colony algorithm,putting forward clustering ant colony algorithm,according to the characteristics of inspection points which are distributed in different buildings.In the interior of each building,clustered in different floors.In this way,the large-scale path optimization problem is transformed into small-scale problem,and the running time of the algorithm is reduced.For the shortcomings of the search space of the clustering ant colony algorithm become small,proposed a hybrid algorithm based on clustering processing ant colony algorithm and multi population genetic algorithm.(3)Design and Implementation of Task Path Optimization Management Module in Housing Defect Management System.Design and implementation of the three major functional modules of task path optimization management.In the data analysis module,analyze each patrol task received by the inspector and pass the parsed data to the intelligent algorithm module,then calculate the optimal path,last pass the optimal path to the path result analysis module,and the path number is analyzed into the inspection task.The planning path tasks will be displayed in the inspection main interface of housing defect management system.(4)The effective test of the model and improved ant colony hybrid algorithm.The inspection main interface of the house defect management system provides test data,compare the minimum inspection cost,the algorithm running time and number of iterations to achieve the minimum cost calculated by the improved ant colony algorithm with that of the basic ant colony algorithm.The results proved that the path optimization model and the hybrid ant colony algorithm are effective.