scholarly journals Location Optimization Model of Rural Express Station with Vehicle Routes Consideration

Author(s):  
Weimin Di ◽  
Huiling Wang ◽  
Yaoxue Yue
GCB Bioenergy ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 304-325 ◽  
Author(s):  
Eckart Petig ◽  
Andreas Rudi ◽  
Elisabeth Angenendt ◽  
Frank Schultmann ◽  
Enno Bahrs

2015 ◽  
Vol 24 (2) ◽  
pp. 287-297 ◽  
Author(s):  
Qiu Xie ◽  
Xing Rong Fan ◽  
Qiong He ◽  
Yu Yang

AbstractPresently, most studies focus on the minimization of the costs and negative social effects of the location of construction waste recycling centers; however, the influence of the location on future operation is usually ignored. Aiming at solving these problems, a location model for the maximization of service reliability was devised. Service reliability includes the recycling reliability of the construction waste and the delivery reliability of the recycled product. Through maximizing service reliability, the location deviation as a result of arrival delay is expected to be reduced and the service reliability improved. Then, two important parameters in our model were solved on the basis of correlative mathematical theories. Finally, an example was implemented to verify our location optimization model. A genetic algorithm was used to obtain optimal solutions, and the solutions were analyzed. Through establishing a location optimization model, a possible better solution to location problems may be obtained to help in implementing location selection for recycling centers.


CICTP 2020 ◽  
2020 ◽  
Author(s):  
Ruonan Zhou ◽  
Liangjie Xu ◽  
Qunjie Peng ◽  
Xiaohan Wang ◽  
Shen Li

Logistics ◽  
2009 ◽  
Author(s):  
Dongping Li ◽  
Ya Wen ◽  
Kefei Yan ◽  
Jun Chen

2013 ◽  
Vol 96 ◽  
pp. 1008-1013 ◽  
Author(s):  
Yingfeng Ji ◽  
Hualong Yang ◽  
Yan Zhang ◽  
Weixin Zhong

2014 ◽  
Vol 521 ◽  
pp. 498-501
Author(s):  
Shao Shuai Song ◽  
Ran Li

Network losses, cost, voltage quality need to be considered when planning the distribution network .Reasonable access of distributed power (DG) can reduce network losses and improve voltage quality. This paper establishes a distributed power siting optimization model aiming to reduce costs, network losses and improve voltage quality. Multi-objective particle swarm optimization (MOPSO) and fuzzy decision optimization technology are combined as a mean for DG siting and constant volume. Objective function is effective and reasonable through practical example.


SIMULATION ◽  
2018 ◽  
Vol 94 (7) ◽  
pp. 625-636 ◽  
Author(s):  
Zhihui Tian ◽  
Wenbin Hou ◽  
Xiaoning Gu ◽  
Feng Gu ◽  
Baozhen Yao

The electric vehicle is seen as an effective way to alleviate the current energy crisis and environmental problems. However, the lack of supporting charging facilities is still a bottleneck in the development of electric vehicles in the Chinese market. In this paper, the cloud model is used to first predict drivers’ charging behavior. An optimization model of charging stations is proposed, which is based on waiting time. The target of this optimization model is to minimize the time cost to electric vehicle drivers. We use the SCE-UA algorithm to solve the optimization model. We apply our method to Dalian, China to optimize charging station locations. We also analyze the optimized result with or without behavior prediction, the optimized result of different numbers of electric vehicles, and the optimized result of different cost constraints. The analysis shows the feasibility and advantages of the charging station location optimization method proposed in this paper.


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