Developing an Optimal Location Selection Methodology of Unmanned Parcel Service Box

Author(s):  
Hyangsuuk Lee ◽  
◽  
Maowei Chen ◽  
Sangho Choo
2019 ◽  
Vol 8 (4) ◽  
pp. 9465-9471

This paper presents a novel technique based on Cuckoo Search Algorithm (CSA) for enhancing the performance of multiline transmission network to reduce congestion in transmission line to huge level. Optimal location selection of IPFC is done using subtracting line utilization factor (SLUF) and CSA-based optimal tuning. The multi objective function consists of real power loss, security margin, bus voltage limit violation and capacity of installed IPFC. The multi objective function is tuned by CSA and the optimal location for minimizing transmission line congestion is obtained. The simulation is performed using MATLAB for IEEE 30-bus test system. The performance of CSA has been considered for various loading conditions. Results shows that the proposed CSA technique performs better by optimal location of IPFC while maintaining power system performance


2009 ◽  
Vol 21 (8) ◽  
pp. 1162-1177 ◽  
Author(s):  
Yunjun Gao ◽  
Baihua Zheng ◽  
Gencai Chen ◽  
Qing Li

2015 ◽  
Vol 298 ◽  
pp. 98-117 ◽  
Author(s):  
Yunjun Gao ◽  
Shuyao Qi ◽  
Lu Chen ◽  
Baihua Zheng ◽  
Xinhan Li

2018 ◽  
Vol 10 (8) ◽  
pp. 2926 ◽  
Author(s):  
Ji Chen ◽  
Jinsheng Wang ◽  
Tomas Baležentis ◽  
Fausta Zagurskaitė ◽  
Dalia Streimikiene ◽  
...  

The teahouse market has seen an expansion across various countries. In order to identify the most reasonable paths for development, the choice of location for the outlets needs to account for a number of conflicting criteria. Therefore, the multicriteria approach is required to effectively handle the location selection problem. In this paper, we develop a multicriteria framework for teahouse selection and apply it in the context of Lithuania. The indicator system is set up in order to capture the different aspects of the candidate locations. We also apply two multicriteria decision-making techniques (the evaluation based on distance from average solution (EDAS) method and the weighted aggregated sum product assessment with normalization (WASPAS-N) method) in order to ensure the robustness of the results. The weights of criteria were determined based on the expert survey. In addition, a Monte Carlo simulation was applied to check the sensitivity in changes of the criterion weights. The empirical application demonstrated validity of the proposed approach in choosing the optimal location of a teahouse.


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