| Service facilities are the carrier of human activities,reasonable allocation of service facilities,and improving service facilities' utilization efficiency after spatial allocation can improve the idleness and scarcity,which is a frontier issue of ongoing concern in planning,geography,and operational research.Service facilities,including education,culture,and sports,health,commerce,life,etc.,can be divided into "publiccommercial," "town-rural," and "dynamic-static" types,and the allocation rules vary with the type and goal orientation.The increasing integration of urban functional structure is significantly influenced by urban dynamic environmental factors such as commuting between work and residence,traffic tide,etc.The existing spatial allocation of service facilities is mainly based on the index transmission and layout methods under the static mode,which is difficult to fully adapt to the demand of "how to improve further the utilization efficiency of service facilities in megacities," especially the service facilities with solid dynamic sensitivity.The urban spatiotemporal dynamic interaction is a modeling expression of the dynamic urban environment from a finer spatiotemporal scale,which can be used as a new way to optimize allocation further.Then,studying the spatial optimization model of service facilities in the dynamic urban environment from spatiotemporal interaction behavior and spatial optimization theory is of great value to improve service facilities' utilization efficiency.The spatial dynamic allocation model of service facilities is a cross-research direction with planning as the theoretical background,geospatial modeling as the method core,and operational research as the algorithm's breakthrough point.Its essence is the combination optimization problem of multiple time slots containing spatial factors,also is a typical high-dimensional and multi-peak spatial optimization problem.The spatial allocation of service facilities is a typical spatial NP-Hard problem,an essential direction of geographic modeling research and breakthrough computing performance.When multiple time slots variables are incorporated,the scale of solving data increases geometrically,leading to a larger calculation scale.Therefore,exploring new optimization theory can improve the search accuracy of the spatial dynamic allocation model of service facilities and propose new methods to alleviate the "length disaster" and "local search",which have significant theoretical and application value.This paper proposes a new search method to search for high-quality spatial allocation solutions,and integrates the new ideas of the dynamic urban environment and quantum evolution mechanism,and studies the concept model framework of spatial allocation of service facilities,the spatial layout optimization model of new service facilities,and the spatial relocation optimization model of service facilities,and improves the spatial optimization algorithm of service facilities under the action of quantum evolution mechanism.This paper integrates the quantum evolution mechanism to improve the accuracy and efficiency of dynamic spatial allocation of service facilities.In this paper,we take Nanjing as a distinct study area,based on the spatial distribution data of multiply time slots active population and multiply time slots traffic route planning data,and select public charging stations and emergency service facilities as examples.The research on multi-objective spatial optimization layout and single-objective spatial relocation scheduling are carried out.The specific research contents include as follows.(1)We design a concept model framework for spatial allocation optimization of service facilities prepared from three levels of model indicators,model rules,and model algorithms to form a conceptual model framework for spatial allocation optimization of service facilities.The framework provides a unified paradigm basis for subsequent service facility evaluation,layout optimization,and model designing.(2)We study the spatial dynamic layout optimization model of new service facilities under a vibrant urban environment and select the public charging station service facilities as typical service facilities to carry out a case study on optimizing the new layout of urban public charging station service facilities multiobjective guidance.(3)We study the spatial relocation optimization model of service facilities in the dynamic urban environment and select the urban emergency service facilities as typical service facilities to carry out a case study of spatial relocation scheduling optimization of urban emergency service facilities under the goal of maximizing equality.(4)We explore and construct a spatial optimization algorithm of service facilities that integrates quantum evolution mechanism.Based on previous quantum evolutionary algorithms and quantum real-coding evolutionary algorithms,the quantum evolutionary mechanism of qubits,quantum gates,and state-space control and transformation are integrated into the genetic algorithm,reproduce the real-coding quantum evolutionary algorithm,and prove its advantages in search efficiency and search accuracy.Finally,we form the Dynamic Total Constrained Integer Coding Quantum Evolutionary Algorithm(DTC-ICQEA)and apply the algorithm to solve service facilities' spatial relocation optimization problem in the dynamic urban environment.This paper's research results mainly include:(1)Based on the concept model framework,the dynamic spatial configuration of emergency service facilities and public charging station service facilities is carried out,and the spatial allocation results under different goal orientations are obtained.(2)For the multi-objective spatial layout optimization configuration of public charging station service facilities,multi-group Pareto optimal solutions are generated.Compared with the traditional static spatial allocation method,the dynamic spatial allocation method can effectively improve the utilization efficiency of the configured service facilities.The population coverage rate is increased by 27.5% compared with the traditional method.(3)After calculating the spatial relocation optimization model of the service facilities in the dynamic urban environment for emergency services,the equity is improved by 40% compared with the traditional static configuration method.(4)The quantum evolution mechanism is introduced to enhance the DTC-ICQEA,which breaks through the Dynamic Total Constrained Integer Coding Genetic Algorithm(DTC-ICGA)is easy to fall into the local optimum solving high-dimensional problems.The search accuracy is significantly improved.The fairness is increased by 60%.The search efficiency is also improved considerably,which shows that the quantum optimization mechanism has excellent potential in spatial optimization problems.In summary,this paper constructs an optimization model of dynamic spatial allocation,which is more effective in utilization efficiency and fairness than traditional static allocation.This paper develops the spatial allocation model of service facilities integrated into the dynamic urban environment.The spatial allocation model of service facilities is developed from static to dynamic,from spatial layout to spatial interaction,and formed a dynamic urban environmental evaluation and optimization model,which is of great value for making special planning of urban service facilities and improving the utilization efficiency of service facilities after planning.The models and examples in this paper have the generalizability of types and regions.They can be extended to multiple types of service facilities and cities,which can provide decision-making for planning urban special service facilities and the development of smart cities.In this paper,quantum evolution mechanism is introduced into spatial optimization research,which provides a method with higher search accuracy for the study of spatial dynamic spatial optimization of service facilities,improves the defect of insufficient search accuracy of the traditional evolutionary algorithm in high-dimensional multi-peak spatial optimization problems,and makes efforts for the development of geospatial quantum computing. |
PDF Full Text Request