Integrated Data Mining and TOPSIS Entropy Weight Method to Evaluate Logistics Supply and Demand Efficiency of a 3PL Company

Yan, Xintong; Gong, Jian; He, Jie; Zhang, Hao; Zhang, Changjian; Liu, Ziyang

doi:10.1155/2020/7057143

Cited by 3 publications

(4 citation statements)

References 53 publications

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“…of data objects by the K-means [33]. According to Yan et al (2020) [44], this paper took Euclidean distance as a calculating standard because of its reliability and generality.…”

Section: K-means Clustersmentioning

confidence: 99%

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Exploring Relationships between Months and Different Crash Types on Mountainous Freeways Using a Combined Modeling Approach

Zhang

Bai

et al. 2022

Journal of Advanced Transportation

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Investigating the relationship between the months and traffic crashes is a foremost task for the safety improvement of mountainous freeways. Taking a mountainous freeway located in China as an example, this paper proposed a combined modeling framework to identify the relationships between months and different crash types. K-means and Apriori were initially used to extract the monthly distribution patterns of different types of crashes. A graphical approach and a risk calculation equation were developed to assess the output of K-means and Apriori. Then, using the assessment results as the input, a logistic regression model was constructed to quantify the effects of each month on crashes. The results indicate that the monthly distribution patterns of different crash types are inconsistent, i.e., for a specific month, the high risk of a certain crash type may be covered up if experts only focus on the total number of crashes. Moreover, when identified as high-risk months by K-means and Apriori, the crash-proneness will significantly increase several times than months identified as high-risk by only one of K-means and Apriori, thereby illustrating the superior performance of the mix-method. The conclusions can assist local relevant organizations in formulating strategies for preventing different types of traffic crashes in different months (e.g., the risk of rear-end crashes in August, the risk of fixed-object hitting crashes in February, and the risk of overturning crashes in October) and provide a methodological reference for relevant studies in other regions.

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“…of data objects by the K-means [33]. According to Yan et al (2020) [44], this paper took Euclidean distance as a calculating standard because of its reliability and generality.…”

Section: K-means Clustersmentioning

confidence: 99%

“…e key advantage of using Apriori is that it can be measured by its support and confidence. Support (s) can be used to determine the frequency of a given dataset, while confidence (c) determines the frequency of Y in transactions containing X. e forms of support and confidence are defined as follows [44]:…”

Section: Apriori Rulesmentioning

confidence: 99%

Exploring Relationships between Months and Different Crash Types on Mountainous Freeways Using a Combined Modeling Approach

Zhang

Bai

et al. 2022

Journal of Advanced Transportation

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“…Step ( 7) is to calculate the matrix at the relative weight value ( ) presented in equation (10). Furthermore, Step ( 8) is normalizing the relative weight values ( ) and ( ) to become the relative weights ( ) by taking the average of the two values.…”

Section: ( ) =mentioning

confidence: 99%

“…3PL provider performance evaluation is a crucial evaluation process in supply chain management [9]. The provider performance evaluation process is used to measure performance and determine follow-up on necessary things [10]. This activity is used to ensure customer needs have been met.…”

Section: Introductionmentioning

confidence: 99%

Integration of Rough SWARA and COPRAS in the Performance Evaluation of Third-Party Logistics Providers

Rosiana

Garside²,

Amallynda

2021

JTI

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Currently, the use of logistics service providers in companies has become a decision chosen by several companies. Companies use Third Party Logistics (3PL) to focus more on other essential activities in the company. Evaluating the performance of a 3PL provider is an essential process in determining performance of a 3PL provider. A wrong evaluation process could lead to company’s loss. The main objective of this study was to propose a 3PL performance appraisal procedure. This study integrated the Rough method Step-wise Weight Assessment Ratio Analysis (SWARA) and the Complex Proportional Assessment Method (COPRAS) to assess the performance of 3PL providers. The SWARA Rough method was used to assess the ranking of the criteria. The results of the Rough SWARA ranking were utilized by the COPRAS method to assess supplier performance. A case study was conducted in an animal feed production company in Indonesia. The results showed that there were criteria for product safety; on-time delivery, responsiveness, and flexibility with the greatest weight among the 16 criteria used.

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Evaluation of Rural Dwellings’ Energy-Saving Retrofit with Adaptive Thermal Comfort Theory

et al. 2021

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The purpose of energy-saving retrofit of rural dwellings is to obtain a more comfortable indoor thermal environment with reasonable investment. The utilization rate of heating and air conditioning equipment for dwellings in poor rural areas is very low, and the buildings operate in natural ventilation mode all year round. Since the existing research on energy-saving retrofit is aimed at air-conditioned buildings, the research methods and results are not applicable to rural dwellings. This paper proposes a set of energy-saving retrofit evaluation methods suitable for natural ventilation buildings and applies it to the research on energy-saving retrofit of rural dwellings in cold climate regions of China. The specific process is as follows: First, this paper analyzed the current situation using field research and established a typical building model. Second, the DesignBuilder software was used to simulate all 725 schemes. Subsequently, the three main retrofit measures (replacing the external insulation windows, setting the external wall insulation layer and setting the roof insulation layer) were analyzed separately, and the optimal parameters of each retrofit measure were obtained. Finally, the entropy weight method was used to perform a multi-objective optimization analysis on all retrofit plans. The results show that 6+12A+6-mm insulating glass windows + 50-mm external wall insulation + 90-mm roof insulation is the optimal energy-saving reconstruction scheme. Compared with the benchmark building, the energy-saving rate of the optimal scheme is increased by 23.81%, and the annual adaptive thermal discomfort degree-hours are decreased by 13.17%.

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Integrated Data Mining and TOPSIS Entropy Weight Method to Evaluate Logistics Supply and Demand Efficiency of a 3PL Company

Cited by 3 publications

References 53 publications

Exploring Relationships between Months and Different Crash Types on Mountainous Freeways Using a Combined Modeling Approach

Exploring Relationships between Months and Different Crash Types on Mountainous Freeways Using a Combined Modeling Approach

Integration of Rough SWARA and COPRAS in the Performance Evaluation of Third-Party Logistics Providers

Evaluation of Rural Dwellings’ Energy-Saving Retrofit with Adaptive Thermal Comfort Theory

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