An Evaluation Model of Green Coal Supplier for Thermal Power Supply Chain Based on PCA-SVM

Qian Zhang,Hai Shen,Yuanyuan Huo,Kin Keung Lai

doi:10.1155/2021/8827273

Abstract

A thermal power supply chain differs from other supply chains in terms of supplier selection, materials transportation, products marketing, and so on. Therefore, the green coal supplier evaluation model has its own characteristics. Although many methods have been developed to solve the green supplier evaluation problem, little is known about how to evaluate the green coal supplier in the thermal power supply chain. To overcome this drawback, an evaluation index system for the green coal supplier is established, and new indexes such as price based on calorific value, quality indexes based on the designed coal type, and transportation indexes such as transportation carbon footprint and environment indexes are created according to the characteristic of the thermal power supply chain. Then, principal component analysis (PCA) is used to create the main evaluation indexes, and the support vector machine (SVM) is adopted for the evaluation model. Finally, a practical example is applied to show that the model established in this paper outperforms others in evaluation accuracy.

Highlights

Green supply chain, known as “Environmentally Conscious Supply chain,” was first presented by Michigan State University Manufacturing Research Society in 1996 [1]
To address this research gap, in this paper, an evaluation index system for the green coal supplier is established according to the characteristics of the thermal power supply chain. en, the principal component analysis (PCA) is used to search the main evaluation indexes, and the support vector machine (SVM) [24] is adopted for evaluation of the green coal supplier
Analysis. e applications results for each σ are listed in Table 4. e same samples and process are used in a traditional artificial neural network, and the result of testing accuracy is 84.44%

Summary

Introduction

Known as “Environmentally Conscious Supply chain,” was first presented by Michigan State University Manufacturing Research Society in 1996 [1]. Due to its high energy consumption characteristics, coal and power industries are the key areas for emission reduction and environment protection, and building green power supply chains is a key method to solve this problem. By considering economic and environmental indicators, Chen et al [18] integrated ANP and TOPSIS methods to solve green supplier evaluation and selection in brightening film industry. A few research studies investigate this problem by using fuzzy satisfaction methods and only consider economic factors (e.g., quality, price, and delivery time) as criteria for supplier evaluation [22, 23]. Erefore, none of these methods consider the special characteristics of thermal power supply chains, as mentioned above. To address this research gap, in this paper, an evaluation index system for the green coal supplier is established according to the characteristics of the thermal power supply chain.

Establish the Index System

Evaluation Model Based on SVM

Example Application and Analysis

Conclusions