The Siting And Sizing Problem Of The Facility For Flow Demand With Range Constraint

The adoptions of current popular technologies such as drones,charging cars,and laser communications have been severely hindered due to their limited endurance or limited propagation distance.A well-deployed and widely distributed network of relay facilities can effectively extend the reach of their coverage.Given the high construction cost of some relay facilities and the limited demand for services,the rational selection of the location and scale of the relay facilities is of great significance for the development and popularization of these technologies.The siting and sizing planning of the relay facility is different from the classical facility location problem,which is oriented to the flow demand from origin to destination.Based on the characteristics and commonality of the flow-demand location problem,this paper carries out research work on the modeling method and specific application scenarios of the siting and sizing problem of facilities facing to flow-demand with endurance constraints.The main work of this paper is as follows:1.The attributes and activities of the entities included in the location problem of the flow-demand service facility are analyzed.All the constraints involved in the planning problem are classified to constitute the main part of the optimization model.The possible application scenarios and manifestations involved in each type of constraint are summarized,which are used to build the modeling framework of the location model of the flow demand service facility.According to the model framework,the existing flow demand service facility location planning model is concentrated into detail application background.The unresolved problems are pointed out according to the classification from the modeling framework,which are main contents of this paper.2.The siting and sizing problem of service facilities for controllable flow-demand is proposed and discussed in this paper.In this problem,the combination of facility for the flowdemand can be controlled by decision maker.More detail constraints including captured demand constraint,service capacity constraint,and construction and expansion cost constraint are involved in the modeling.To solve the complex programming model,a simulated annealing algorithm is designed.The feasibility and sensitivity of the model and algorithm were tested by the actual background of the border drone patrol network construction.3.The siting and sizing problem of service facilities for autonomous flow-demand is proposed and discussed in this paper.The key issue of the problem is to quantify the utility of the demand for different facility combinations when the flow demands have their own preference.Therefore,we approached the utility theory based on the load situation of the service facilities in the network.The equilibrium state of the flow-demand distribution in the network with the given siting and sizing scheme of service facility is defined.The optimization model of siting and sizing of facility for the autonomous flow demand is designed.To solve the optimization model with complex relationship of flow demand distribution,a two-stage genetic algorithm and a deep-search based heuristic algorithm that can solve the planning problem in a limited time are designed.The feasibility and effectiveness of the model and algorithm are compared with the practical case of the Hebei Highway network and the stochastic generation networks.Through the management and sensitivity analysis,some guiding suggestions for the construction of facilities in practical situation are obtained.4.The siting and sizing problem of facilities for flow-demand with demand cost is proposed and discussed.The possible relationships between the additional cost and the change of the flow demand in the network are discussed.The modeling and analysis of the controlled and the autonomy demand are carried out respectively.A single-stage genetic algorithm and a neighborhood search algorithm are designed to solve complex planning models with demand cost,autonomous flow demand distribution and multiple other constraints.The application case of electric vehicles promotion in Hunan Highway network was applied to compare the effectiveness of the model and the algorithm.The management analysis was carried out according to the results.At the same time,considering the improvement effect of the intelligent optimization algorithm on the given solutions,the possibility and effectiveness of the combination of the heuristic algorithm,the genetic algorithm and the neighborhood search algorithm are discussed.