To reduce flood disasters and optimize of the comprehensive benefit of the water basin, the allocation of regional flood drainage rights is of great significance. Using the top-down allocation mode, we consider the in...
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To reduce flood disasters and optimize of the comprehensive benefit of the water basin, the allocation of regional flood drainage rights is of great significance. Using the top-down allocation mode, we consider the influence of the social, economic, and ecological environments, flood drainage demand and efficiency, and other factors on the allocation of flood drainage rights. A bi-level multi-objective programming model from the perspective of fairness and efficiency is established for the allocation. The Sunan Canal is taken as a typical case study. The model is solved by the multi-objective optimal allocation method and the master-slave hierarchical interactive iteration algorithm. After three iterations of the initial solution, the allocation of flood drainage rights in six flood control regions finally reach an effective state. The results of the model were compared with results based on historical allocation principles, showing that the bi-level multi-objective programming model, based on the principles of fairness and efficiency, is more in line with the current social and economic development of the canal. In view of the institutional background of water resources management in China and the flood drainage pressure faced by various regions, the allocation of flood drainage rights should be comprehensively considered in combination with various factors, and the market mechanism should be utilized to optimize the allocation.
Based on the design principle of minimizing the automotive exhaust emissions and the total impedance of the road network, an urban road traffic signal control method of bi-level multi-objective programming model is es...
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ISBN:
(纸本)9789811035517;9789811035500
Based on the design principle of minimizing the automotive exhaust emissions and the total impedance of the road network, an urban road traffic signal control method of bi-level multi-objective programming model is established by designing the heuristic particle swarm optimization (PSO) algorithm. First of all, the upper-levelmodel which combined the vehicle emissions model and system optimum assignment model is built, and the lower-levelmodel is built based on minimizing the sum of the link travel time function integral. Then, the heuristic PSO algorithm is designed and transformed to solve upper-level and lower-levels model iteratively by two PSO algorithms. Ultimately, by altering the weight parameters of the upper model, the model is dealt with separately in case of single target and multi-target, the optimization results of which is compared with the VISSIM simulation results and the optimization results by means of heuristic genetic algorithm. The simulation results show that bi-levelmulti-objective control method, which could improve the operating quality of road network, is of great optimization ability and can effectively reduce the automotive exhaust emissions and the total impedance of the road network.
It is important for urban traffic micro-circulation to improve the density of urban branch road networks by opening roads inside blocks. To reasonably optimize the micro-circulation road network in the open block area...
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It is important for urban traffic micro-circulation to improve the density of urban branch road networks by opening roads inside blocks. To reasonably optimize the micro-circulation road network in the open block area, a bi-level multi-objective programming model that considers traffic pollution and intersection delays was developed. In this paper, the goals of minimizing traffic pollution and total travel cost are added to the upper-levelprogrammingmodel and the user equilibrium assignment model with the consideration of intersection delay was presented as the lower-levelprogrammingmodel. A modified genetic algorithm (GA) embedded with the Frank-Wolfe algorithm was designed to solve the established model. The traffic conditions of arterial roads and micro-circulation branch roads before and after optimizing the micro-circulation block road network were compared and analyzed by a numerical example. The results demonstrated that the bi-levelprogrammingmodel can effectively determine the traffic direction of branch roads and the forbidden situation of intersections in the micro-circulation network. Compared with the closed block, the average saturation of the main trunk road decreased from 0.97 to 0.83 with a decline ratio of 14.43% after optimizing the micro-circulation network in the open block area;the average saturation of the secondary trunk road decreased from 0.86 to 0.77, with a decline ratio of 10.47%. The travel time cost decreased by approximately 6.55%, and the traffic pollution decreased by approximately 3.40%, which verified the optimization effect of the model and the algorithm.
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