In the context of low-carbon city development, this paper further implements a rail transit passenger flow forecasting method to optimize energy consumption by combining the MMA allocation model with a two-tier planni...
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In the context of low-carbon city development, this paper further implements a rail transit passenger flow forecasting method to optimize energy consumption by combining the MMA allocation model with a two-tier planning model for carbon emission control. Through this approach, this paper not only fills the gap of rail transportation planning theories and methods compatible with low-carbon city development, but also emphasizes the importance of energy consumption in transportation planning. Based on a two-tier planning model, this paper considers the Starkberg game between multi-modal and multi-type passenger flow forecasting of rail transit and CO2 emissions of integrated transportation systems. By optimizing the allocation of users in the transportation network from the perspective of both users and planners, while optimizing the CO2 emissions of the integrated transportation system, the dual optimization of energy consumption and environmental benefits is achieved. The method will also be tested in Shanghai, and this paper will comparatively study three different carbon emission control schemes. By assigning passenger flows to the entire transportation system network in Shanghai based on information from the Fourth Integrated Transport Survey, including passenger flows on each road in the road network, passenger flows on each rail line, and characteristic indicators, this paper provides a reliable data base. This study provides a solid foundation for planning the layout of rail transit in a low-carbon mode and makes a positive contribution to sustainable urban development by optimizing energy consumption.
This paper studies a discontinuous lane reservation problem considering the heterogeneous traffic demand containing both vehicles with general purposes and vehicles with special tasks. The modeling difference between ...
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This paper studies a discontinuous lane reservation problem considering the heterogeneous traffic demand containing both vehicles with general purposes and vehicles with special tasks. The modeling difference between these two types of vehicles is that only vehicles with special tasks have time budgets for their trip. The objective is to satisfy the target travel time of the vehicles with special tasks through the lane reservation scheme, and to minimize the negative impact on the rest vehicles due to the decrease of the lane number simultaneously. This discontinuous lane reservation problem is formulated as a discrete bi-level programming model, where the upper level determines which road segments could be reserved, while the lower level optimizes the route choices under the given lane reservation scheme. A nested artificial bee colony and Frank-Wolfe algorithm is proposed to solve the model. A numerical experiment with the Sioux-Falls network validates the effectiveness of the proposed model and the efficiency of the solution algorithm.
One way to deal with the future effects of climatic changes on the water resources and to cope with water shortages in basins is to have a clear understanding of the future climate change trends. To this end, this stu...
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One way to deal with the future effects of climatic changes on the water resources and to cope with water shortages in basins is to have a clear understanding of the future climate change trends. To this end, this study proposes an integrated hydrological-water transfer and supply (HWTS) framework including a coupled SWAT-bilevelprogrammingmodel to investigate future optimal water supply between different sectors with regard to transaction right. Indeed, Soil & Water Assessment Tool (SWAT) is applied to project the rate of streamflow under Representative Concentration Pathway scenarios of RCP2.6&RCP4.5 and future periods (2020-2040 & 204(Abbas et al. 2015)2060). In addition, a case study of the Hamoun wetland in southeastern of Iran is considered for calibration and validation of real historical data (2000-2016) and then simulation of future streamflow patterns (2020-2060). Next, simulated streamflow data extracted by SWAT is entered as the input of market based bi-level optimization model so that upper-level manager seeks optimization of the available water level in the reservoirs while the lower-level decision maker tries to minimize the economic loss due to water shortage between different sectors regarding transaction right. However, after solving the model with the Improved Particle Swarm Optimization (IBPSO) technique, the final results show that although not much economic profit will be made, but considering specific management strategies such as demand reduction schemes to conserve more water, the imbalance between supply and demand can be significantly improved.
The facility configuration and layout design of hub stations play an essential role in building a practical and cost-efficient hub station system. In general practice, bi-level programming models are implemented based...
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The facility configuration and layout design of hub stations play an essential role in building a practical and cost-efficient hub station system. In general practice, bi-level programming models are implemented based on specific objectives and constraints. In this study, an upper-levelmodel is used to solve the facility configuration problem, which is constructed based on the predetermined facility types to calculate the quantity of each facility by three objectives, including the number of passengers queueing in line, passengers' average waiting time in the queueing system and the cost of facilities. A genetic simulated annealing (GSA) algorithm based on the. -constraints method is presented to optimize the upper-levelmodel. A lower-levelmodel is used to solve the facility layout problem. An optimization solver, named CPLEX, is applied in the lower-levelmodel to calculate the abscissas and ordinates of the facility location after determining the facility configuration in the upper-levelmodel. A case study of the Lanzhou West station in Northern China is demonstrated to verify the efficiency of the optimal solution from the bi-levelmodel by using a commercial pedestrian simulation software, MASSMOTION. This study reveals an innovative method for optimizing station facility configuration and layout by using the heuristic novel algorithm, a discrete event simulation technology and effective utilization of the Building Information model (biM) data.
Aiming at the problem of asymmetry information between the owner and the contractor in construction project. In order to motivate the contractor to produce, taking cost, quality and progress as incentive factors, and ...
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ISBN:
(纸本)9781728155883
Aiming at the problem of asymmetry information between the owner and the contractor in construction project. In order to motivate the contractor to produce, taking cost, quality and progress as incentive factors, and considering the interests of both parties, based on the three factors' relationship function, the bi-level decision-making model of the multi-factor incentive pricing is built. The upper model takes the incentive coefficients as the decision-making variables and maximize the expected utility of the owner as the objective, the lower model takes the efforts' degree as the decision-making variables and maximize the expected revenue of the contractor as the objective. The model is solved with the aid of one example by genetic algorithm and the optimal incentive coefficients are obtained. Finally, through numerical simulation, the variation laws of the incentive coefficients under different influencing factors are obtained.
The logistics distribution of prefabricated components is an important issue facing the realization of "building industrialization" in China. However, the current transportation scheduling of prefabricated c...
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ISBN:
(纸本)9781728132686
The logistics distribution of prefabricated components is an important issue facing the realization of "building industrialization" in China. However, the current transportation scheduling of prefabricated components is mostly based on the experience and subjective consciousness of dispatchers, and lacks effective scientific and systematic analysis. In order to solve this problem, this paper proposes a bi-level programming model based on time satisfaction. In the upper model, combined with the transportation characteristics of prefabricated components, a hybrid time satisfaction function is proposed. The total transportation cost and time satisfaction penalty cost are the minimum optimization targets to determine the OD matrix of the transportation network. In the lower model, the actual road network traffic conditions are fully considered, and the user equilibrium (UE) is used to distribute the prefabricated component transportation network traffic. In order to solve the model, a heuristic algorithm combining genetic algorithm and Partan Frank-Wolfe algorithm is designed and verified by case.
In recent years,China's society has developed rapidly,the high-speed railway network has become more and more perfect,and the competition between high-speed rail and civil aviation has become increasingly *** the ...
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In recent years,China's society has developed rapidly,the high-speed railway network has become more and more perfect,and the competition between high-speed rail and civil aviation has become increasingly *** the country's newly introduced national transportation development plan,the development of the comprehensive transportation system is placed in an important *** operation of the empty railway is an important part of comprehensive transportation,and it has attracted more and more *** the development of air-rail transportation,the decisive role is still in the formulation of fares.A cheaper fare can attract huge passenger traffic,so it is necessary to explore a reasonable method of fare *** paper chooses to establish a bi-level programming model,and set the upper-level planning objective function to maximize the ticket benefit of the relevant departments of the empty-rail intermodal *** objective function of the lower-level planning is to minimize the passenger's general travel cost and solve the model,so as to obtain a relatively complete The method for formulating fares for air and rail transportation provides a reference for the formulation of air and rail freight fares in ***,the paper validates the model based on the air-rail combined transport line from Beijing to Sanya.
Utilizing the data obtained from both scanning and counting sensors is critical for efficiently managing traffic flow on roadways. Past studies mainly focused on the optimal layout of one type of sensor, and how to op...
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Utilizing the data obtained from both scanning and counting sensors is critical for efficiently managing traffic flow on roadways. Past studies mainly focused on the optimal layout of one type of sensor, and how to optimize the arrangement of more than one type of sensor has not been fully researched. This paper develops a methodology that optimizes the deployment of different types of sensors to solve the well-recognized network sensors location problem (NSLP). To answer the questions of how many, where and what types of sensors should be deployed on each particular link of the network, a novel bi-level programming model for full route observability is presented to strategically locate scanning and counting sensors in a network. The methodology works in two steps. First, a mathematical program is formulated to determine the minimum number of scanning sensors. To solve this program, a new 'differentiating matrix' is introduced and the corresponding greedy algorithm of 'differentiating first' is put forward. In the second step, a scanning map and an incidence matrix are incorporated into the program, which extends the theoretical model for multiple sensors' deployment and provides the replacement method to reduce total cost of sensors without loss of observability. The algorithm developed at the second step involved in two coefficient matrixes from scanning map and incidence parameter enumerate all possibilities of replacement schemes so that cost of different combination schemes can be compared. Finally, the proposed approach is demonstrated by comparison of Nguyen-Dupuis network and real network, which indicates the proposed method is capable to evaluate the trade-off between cost and all routes observability.
The routing and spectrum assignment problems in elastic optical networks are well-known NP-hard problem, and are even more complex and challenging when the energy consumption is taken into account. To tackle this chal...
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The routing and spectrum assignment problems in elastic optical networks are well-known NP-hard problem, and are even more complex and challenging when the energy consumption is taken into account. To tackle this challenging problem, we establish a bi-level programming model with the energy consumption of the optical networks and the maximum index of used frequency slots as the leader's and follower's objectives to be minimized, respectively, which are used to determine the optimal schemes of routing and spectrum assignments. To solve the model effectively, a hybrid genetic algorithm framework integrating a heuristic algorithm into a genetic algorithm is proposed. We use heuristic algorithm to sort the connection requests and design a genetic algorithm with tailor-made crossover, mutation and local search operator to look for an optimal routing and spectrum assignment scheme. Finally, simulation experiments are conducted, and the experimental results indicate the effectiveness of the proposed model and algorithms.
By analyzed the transport mode division of Lan-xin Corridor, and according to the way each passenger transport products that can provided by different modes, the transport modes competition was classified as passenger...
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ISBN:
(纸本)9781509011025
By analyzed the transport mode division of Lan-xin Corridor, and according to the way each passenger transport products that can provided by different modes, the transport modes competition was classified as passenger transport product competition. On this basis, built the bi-level programming model of passenger fares in Lanzhou to Xinjiang high-speed railway based on products competition: the upper level aims to maximize the railway revenue and lower level aims to minimize the passengers cost under the various conditions of passenger transport products and improved particle swarm algorithm be used to solve the model. The results show that the real fare of the first class and the second class is lower than the optimal results, and the fare can be adjusted timely according to the conditions of passenger flow cultivation in the subsequent operation.
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