scholarly journals Optimizing Bus Line Based on Metro-Bus Integration

2020 ◽  
Vol 12 (4) ◽  
pp. 1493 ◽  
Author(s):  
Junjun Wei ◽  
Kejun Long ◽  
Jian Gu ◽  
Qingling Ju ◽  
Piao Zhu
Keyword(s):  
Resource Allocation ◽  
Optimization Model ◽  
Geographical Location ◽  
Optimization Method ◽  
Line Number ◽  
Competition And Cooperation ◽  
Travel Efficiency ◽  
Geographical Space ◽  
Metro System

Metros are usually built and added on the basis of a completed bus network in Chinese cities. After the metro construction, it is faced with the problem of how to adjust and optimize the original bus lines based on the new metro system. This research mainly proposes a bus line optimization method based on bus and metro integration. In the consideration of the geographical space, the cooperation and competition relationship between bus and metro lines is qualitatively introduced according to the geographical location and service range of metro (800 m radius) and bus (500 m radius) stations. The competition and cooperation indexes are applied to define the co-opetition relationship between bus and metro lines. The bus line optimization model is constructed based on the co-opetition coefficient and Changsha Metro Line Number 2 is chosen as a case study to verify the optimization model. The results show that the positive competition, efficient cooperation, and travel efficiency between metro and bus has been significantly enhanced after optimization. Moreover, this paper provides a reasonable reference for public transport network planning and resource allocation.

scholarly journals Optimization Analysis of Supply Chain Resource Allocation in Customized Online Shopping Service Mode

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Jianming Yao ◽  
Mengjie Gu
Keyword(s):  
Resource Allocation ◽  
Supply Chain ◽  
Optimization Model ◽  
Online Shopping ◽  
Optimization Method ◽  
Ant Algorithm ◽  
Operational Characteristics ◽  
Service Patterns ◽  
Shopping Environments ◽  
Service Mode

For an online-shopping company, whether it can provide its customers with customized service is the key to enhance its customers’ experience value and its own competence. A good customized service requires effective integration and reasonable allocation of the company’s supply chain resources running in the background. Based on the analysis of the allocation of supply chain resources in the customized online shopping service mode and its operational characteristics, this paper puts forward an optimization model for the resource allocation and builds an improved ant algorithm to solve it. Finally, the effectiveness and feasibility of the optimization method and algorithm are demonstrated by a numerical simulation. This paper finds that the special online shopping environments lead to many dynamic and uncertain characters of the service demands. Different customized service patterns and their combination patterns should match with different supply chain resource allocations. The optimization model not only reflects the required service cost and delivery time in the objective function, but also considers the service scale effect optimization and the relations of integration benefits and risks. The improved ant algorithm has obvious advantages in flexibly balancing the multiobjective optimizations, adjusting the convergence speed, and adjusting the operation parameters.

Optimization Method Based on Genetic Evolution for Multiple-Stage Coordinate Mining of Multiple Mining Areas with same Coal

2013 ◽  
Vol 807-809 ◽  
pp. 2460-2469
Author(s):  
Qiang Zeng ◽  
Ze Bin Zhang ◽  
Zu Qiang Xiong ◽  
De Quo Xiong
Keyword(s):  
Optimization Model ◽  
Mathematical Optimization ◽  
Optimization Method ◽  
Great Difficulty ◽  
Simplified Model ◽  
Genetic Evolution ◽  
Total Sale ◽  
Mining Areas ◽  
Mathematical Optimization Model

Aiming at the multiple-stage coordinate mining problem for multiple mining areas with same coal, an optimization method based on genetic evolution is proposed. Firstly, a mathematical optimization model with the objective to maximize the total sale of synthetic coal is established. Then, the model is simplified to another mathematical optimization model with the objective to maximize price of synthetic coal of each stage because of the great difficulty to resolve the model. Thirdly, a genetic algorithm for coordinate mining of multiple mining areas is presented and designed to resolve the simplified model. Finally, the effectiveness of the proposed method is validated by case study.

scholarly journals Sensor Networks Hierarchical Optimization Model for Security Monitoring in High-Speed Railway Transport Hub

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Zhengyu Xie ◽  
Yong Qin
Keyword(s):  
Sensor Networks ◽  
Optimization Model ◽  
High Speed ◽  
Optimization Problem ◽  
Optimization Method ◽  
Hierarchical Optimization ◽  
Railway Transport ◽  
High Speed Railway ◽  
Security Monitoring

We consider the sensor networks hierarchical optimization problem in high-speed railway transport hub (HRTH). The sensor networks are optimized from three hierarchies which are key area sensors optimization, passenger line sensors optimization, and whole area sensors optimization. Case study on a specific HRTH in China showed that the hierarchical optimization method is effective to optimize the sensor networks for security monitoring in HRTH.

Optimization Method for Robust Continuous Parameter Design in the Target-being-Best Based on Genetic Evolution

2014 ◽  
Vol 1049-1050 ◽  
pp. 1272-1280
Author(s):  
Qiang Zeng ◽  
Ling Shen ◽  
Ze Bin Zhang
Keyword(s):  
Genetic Algorithm ◽  
Theoretical Calculation ◽  
Optimization Model ◽  
Optimization Method ◽  
Parameter Design ◽  
Genetic Evolution ◽  
Quality Loss ◽  
Average Quality ◽  
Continuous Parameter

Aiming at the problem of robust continuous parameter design in the Target-being-best, in which the output value can be obtained by theoretical calculation, an optimization method based on genetic evolution is proposed. Firstly, the researched problem is described mathematically and an optimization model is established with the objective to minimize the average quality loss of a sample. Secondly, the optimization method based on genetic evolution for the researched problem is proposed. Thirdly, the genetic algorithm for robust continuous parameter design in the Target-being-best is presented and designed. Finally, the effectiveness of the proposed method is validated by case study.

Robust Optimization Model for Primary and Backup Resource Allocation in Cloud Providers

2021 ◽  
pp. 1-1
Author(s):  
Fujun He ◽  
Takehiro Sato ◽  
Bijoy Chand Chatterjee ◽  
Takashi Kurimoto ◽  
Urushidani Shigeo ◽  
...  
Keyword(s):  
Resource Allocation ◽  
Robust Optimization ◽  
Optimization Model ◽  
Cloud Providers
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