Energy-saving optimization strategy of multi-train metro timetable based on dual decision variables: A case study of Shanghai Metro line one

2021 ◽  
Vol 17 ◽  
pp. 100234
Author(s):  
Jinlin Liao ◽  
Feng Zhang ◽  
Shiwen Zhang ◽  
Guang Yang ◽  
Cheng Gong
Keyword(s):  
Energy Saving ◽  
Optimization Strategy ◽  
Decision Variables ◽  
Shanghai Metro

A hybrid optimization strategy for the maintenance of the wheels of metro vehicles: Vehicle turning, wheel re-profiling, and multi-template use

2017 ◽  
Vol 232 (3) ◽  
pp. 832-841 ◽  
Author(s):  
Wei Zhu ◽  
Di Yang ◽  
Jun Huang
Keyword(s):  
Optimal Solution ◽  
Hybrid Optimization ◽  
Optimization Approach ◽  
Optimization Strategy ◽  
Wheel Wear ◽  
Rail Systems ◽  
Common Strategy ◽  
Shanghai Metro ◽  
Open Nature

The wheel–rail contact relationship has a great impact on the security and reliability of metro vehicles in service. In particular, wear modeling and maintenance optimization of the wheels play significant roles with regard to both safety and cost. However, it is difficult to provide a satisfactory model of wheel wear because of the open nature of real wheel–rail systems and the constantly varying environmental conditions in which they operate. Historically, re-profiling, which also has its limitation to some extent, was adopted as a common strategy to restore the original profiles of the worn wheels. Acknowledging that re-profiling is not the only strategy for dealing with wheel wear, the authors of this study have developed a more advanced optimization approach that includes two more strategies, namely, vehicle turning and multi-template use, to give as near an optimal solution as possible. Vehicle turning refers to the reversal of the vehicle’s orientation on the rail, whereas multi-template use refers to the situation where different re-profiling templates are used alternately. In this paper, re-profiling, vehicle turning, and multi-template use have been discussed separately. Then a hybrid optimization strategy for the maintenance of the wheels of metro vehicles has been proposed, with the aim of maximizing the wheel life while minimizing the relevant costs. An initial case study on the Shanghai Metro system shows that the proposed approach is able to provide a more reasonable solution for the optimization of the maintenance strategies.

scholarly journals A Queuing Network Based Optimization Model for Calculating Capacity of Subway Station

2017 ◽  
Vol 2017 ◽  
pp. 1-7
Author(s):  
Hanchuan Pan ◽  
Zhigang Liu
Keyword(s):  
Optimization Model ◽  
Subway Station ◽  
Queuing Model ◽  
Selection Probability ◽  
Evaluation Indexes ◽  
State Dependent ◽  
Decision Variables ◽  
Proposed Model ◽  
Shanghai Metro

Capacity of subway station is an important factor to ensure the safety and improve the transportation efficiency. In this paper, based on the M/G/C/C state-dependent queuing model, a probabilistic selection optimization model is proposed to assess the capacity of the station. The goal of the model is to maximize the output rate of the station, and the decision variables of the model are the selection results of the passengers. Finally, this paper takes a subway station of Shanghai Metro as a case study and calculates the optimal selection probability. The proposed model could be used to analyze the average waiting time, congestion probability, and other evaluation indexes; at the same time, it verifies the validity and practicability of the model.

Energy saving in the tissue industry: technical and economic aspects of a case study

2006 ◽  
Vol 14 (2) ◽  
pp. 185-193 ◽  
Author(s):  
R. Gabbrielli ◽  
C. Medeot ◽  
D. Miconi
Keyword(s):  
Energy Saving ◽  
Economic Aspects

scholarly journals Two-stage multi-tasking transform framework for large-scale many-objective optimization problems

2021 ◽  
Author(s):  
Lu Chen ◽  
Handing Wang ◽  
Wenping Ma
Keyword(s):  
Large Scale ◽  
Original Problem ◽  
Optimization Problems ◽  
Reference Points ◽  
Optimization Strategy ◽  
Two Stage ◽  
Decision Space ◽  
Second Stage ◽  
Decision Variables ◽  
Objective Space

AbstractReal-world optimization applications in complex systems always contain multiple factors to be optimized, which can be formulated as multi-objective optimization problems. These problems have been solved by many evolutionary algorithms like MOEA/D, NSGA-III, and KnEA. However, when the numbers of decision variables and objectives increase, the computation costs of those mentioned algorithms will be unaffordable. To reduce such high computation cost on large-scale many-objective optimization problems, we proposed a two-stage framework. The first stage of the proposed algorithm combines with a multi-tasking optimization strategy and a bi-directional search strategy, where the original problem is reformulated as a multi-tasking optimization problem in the decision space to enhance the convergence. To improve the diversity, in the second stage, the proposed algorithm applies multi-tasking optimization to a number of sub-problems based on reference points in the objective space. In this paper, to show the effectiveness of the proposed algorithm, we test the algorithm on the DTLZ and LSMOP problems and compare it with existing algorithms, and it outperforms other compared algorithms in most cases and shows disadvantage on both convergence and diversity.

scholarly journals Improvements in Energy Saving and Thermal Environment after Retrofitting with Interior Insulation in Intermittently Cooled Residences in Hot-Summer/Cold-Winter Zone of China: A Case Study in Chengdu

Energies ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2776
Author(s):  
Xin Ye ◽  
Jun Lu ◽  
Tao Zhang ◽  
Yupeng Wang ◽  
Hiroatsu Fukuda
Keyword(s):  
Energy Saving ◽  
Thermal Environment ◽  
Real Life ◽  
Average Energy ◽  
Experimental Result ◽  
Cold Winter ◽  
The South ◽  
Indoor Thermal Environment ◽  
Space Cooling

Space cooling is currently the fastest-growing end-user in buildings. The global warming trend combined with increased population and economic development will lead to accelerated growth in space cooling in the future, especially in China. The hot summer and cold winter (HSCW) zone is the most densely populated and economically developed region in China, but with the worst indoor thermal environment. Relatively few studies have been conducted on the actual measurements in the optimization of insulation design under typical intermittent cooling modes in this region. This case study was conducted in Chengdu—the two residences selected were identical in design, but the south bedroom of the case study residence had interior insulation (inside insulation on all opaque interior surfaces of a space) retrofitted in the bedroom area in 2017. In August 2019, a comparative on-site measurement was done to investigate the effect of the retrofit work under three typical intermittent cooling patterns in the real-life scenario. The experimental result shows that interior insulation provides a significant improvement in energy-saving and the indoor thermal environment. The average energy savings in daily cooling energy consumption of the south bedroom is 42.09%, with the maximum reaching 48.91%. In the bedroom with interior insulation retrofit, the indoor temperature is closer to the set temperature and the vertical temperature difference is smaller during the cooling period; when the air conditioner is off, the room remains a comfortable temperature for a slightly longer time.

Technology for energy-saving railway operation through power-limiting brakes—A case study at an urban railway

2014 ◽  
Author(s):  
Takafumi Koseki ◽  
Shoichiro Watanabe ◽  
Yasuhiro Hamazaki ◽  
Keiichiro Kondo ◽  
Tomonori Hasegawa ◽  
...  
Keyword(s):  
Energy Saving ◽  
Railway Operation
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