Wei-Chang Yeh

Prof. Wei-Chang Yeh

Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu City, Taiwan
orcid

Research Focus & Metrics

Academic Career Length

24Years (2003-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 June 2020 in Information Sciences
Verified
Journal Article
Closed access
YZYin Zhang
Yin Zhang
Gai-Ge WangGai-Ge Wang
Gai-Ge Wang
Keqin LiKeqin Li
Keqin Li
WYWei-Chang Yeh
Wei-Chang Yeh
MJMuwei Jian
Muwei Jian
Junyu DongJunyu Dong
Junyu Dong

2 November 2021 in Applied Sciences
Verified
Journal Article
Open access
PDF file
Shi-Yi TanShi-Yi Tan
Shi-Yi Tan
WYWei-Chang Yeh
Wei-Chang Yeh
Transportation planning has been established as a key topic in the literature and social production practices. An increasing number of researchers are studying vehicle routing problems (VRPs) and their variants considering real-life applications and scenarios. Furthermore, with the rapid growth in the processing speed and memory capacity of computers, various algorithms can be used to solve increasingly complex instances of VRPs. In this study, we analyzed recent literature published between 2019 and August of 2021 using a taxonomic framework. We reviewed recent research according to models and solutions, and divided models into three categories of customer-related, vehicle-related, and depot-related models. We classified solution algorithms into exact, heuristic, and meta-heuristic algorithms. The main contribution of our study is a classification table that is available online as Appendix A. This classification table should enable future researchers to find relevant literature easily and provide readers with recent trends and solution methodologies in the field of VRPs and some well-known variants.

1 June 2019 in Information Sciences
Verified
Journal Article
Closed access
ZHZhifeng Hao
Zhifeng Hao
WYWei-Chang Yeh
Wei-Chang Yeh
JWJing Wang
Jing Wang
Gai-Ge WangGai-Ge Wang
Gai-Ge Wang
BSBin Sun
Bin Sun

1 April 2020 in Applied Energy
Verified
Journal Article
Closed access
WYWei-Chang Yeh
Wei-Chang Yeh
MHMin-Fan He
Min-Fan He
CHChia-Ling Huang
Chia-Ling Huang
STShi-Yi Tan
Shi-Yi Tan
XZXianyong Zhang
Xianyong Zhang
LLLi Li
Li Li

1 December 2004 in The International Journal of Advanced Manufacturing Technology
Verified
Journal Article
Closed access
PDF file
WYWei-Chang Yeh
Wei-Chang Yeh

18 August 2016 in IEEE Transactions on Neural Networks and Learning Systems
Verified
Journal Article
Closed access
WYWei-Chang Yeh
Wei-Chang Yeh
Network reliability is an important index to the provision of useful information for decision support in the modern world. There is always a need to calculate symbolic network reliability functions (SNRFs) due to dynamic and rapid changes in network parameters. In this brief, the proposed squeezed artificial neural network (SqANN) approach uses the Monte Carlo simulation to estimate the corresponding reliability of a given designed matrix from the Box-Behnken design, and then the Taguchi method is implemented to find the appropriate number of neurons and activation functions of the hidden layer and the output layer in ANN to evaluate SNRFs. According to the experimental results of the benchmark networks, the comparison appears to support the superiority of the proposed SqANN method over the traditional ANN-based approach with at least 16.6% improvement in the median absolute deviation in the cost of extra 2 s on average for all experiments.