Green supplier selection in straw biomass industry based on cloud model and possibility degree

A systematic work has been presented for condition assessment of suspension bridges in this study. Initially, a four-layer index system is built up. Subsequently, 45 experts are invited to determine the index weights by processing the experts’ opinions using the Group Decision-Making (GDM). The assigned weights seem more reasonable (especially weights of the tower and auxiliary facility) when compared with those in the existing China’s code. Next, assessment algorithms, the Local Variable Weight Model (LVWM) and Normal Cloud Model (NCM), are established based on the characteristics of the bridge condition assessment. The LVWM adjusts weight properly to make assessment results in line with the actual situation under extreme cases. The NCM describes not only the fuzziness but also the randomness in the assessment process. Finally, a case study is illustrated to verify the effectiveness of the methodology. For sake of highlighting the advantages of the LVWM, two more models are subjected to the case study, which are the Constant Weight Model (CWM) and Traditional Variable Weight Model (TVWM). Consequently, the assessment result of the LVWM is more in keeping with the actual situation than those of the CWM or TVWM.

Condition Assessment of Suspension Bridges Using Local Variable Weight and Normal Cloud Model

PurposeFood supply chains (FSCs) are fast becoming more and more complex. Sustainability is a necessary strategy in FSCs to meet the environmental, economic and societal requirements. Industry 4.0 (I4.0) applications for a circular economy (CE) will play a significant role in sustainable food supply chains (SFSCs). I4.0 applications can be used in for traceability, tracking, inspection and quality monitoring, environmental monitoring, precision agriculture, farm input optimization, process automation, etc. to improve circularity and sustainability of FSCs. However, the factors integrating I4.0 and CE adoption in SFSC are not yet very well understood. Furthermore, despite such high potential I4.0 adoption is also met with several barriers. The present study identifies and analyzes twelve barriers for the adoption of I4.0 in SFSC from an CE context.Design/methodology/approachA cause-effect analysis and prominence ranking of the barriers are done using Rough-DEMATEL technique. DEMATEL is a widely used technique that is applied for a structured analysis of a complex problems. The rough variant of DEMATEL helps include the uncertainty and vagueness of decision maker related to the I4.0 technologies.Findings“Technological immaturity,” “High investment,” “Lack of awareness and customer acceptance” and “technological limitations and lack of eco-innovation” are identified as the most prominent barriers for adoption of I4.0 in SFSC.Originality/valueSuccessful mitigation of these barriers will improve the sustainability of FSCs through accelerated adoption of I4.0 solutions. The findings of the study will help managers, practitioners and planners to understand and successfully mitigate these barriers.

Barriers for adoption of Industry 4.0 in sustainable food supply chain: a circular economy perspective

Incorporating the impact of the COVID-19 pandemic on the mask supply chain into our framework and taking mask output as a state variable, our study introduces the differential game to study the long-term dynamic cooperation of a two-echelon supply chain composed of the supplier and the manufacturer under government subsidies. The study elaborates that government subsidies can provide more effective incentives for supply chain members to cooperate in the production of masks compared with the situation of no government subsidies. A relatively low wholesale price can effectively increase the profits of supply chain members and the supply chain system. The joint contract of two-way cost-sharing contract and transfer payment contract can promote production technology investment efforts of the supply chain members, the optimum trajectory of mask production, and total profit to reach the best state as the centralized decision scenario within a certain range. Meanwhile, it is determined that the profits of supply chain members in the joint contract can be Pareto improvement compared with decentralized decision scenario. With the increase of production technology investment cost coefficients and output self-decay rate, mask outputs have shown a downward trend in the joint contract decision model. On the contrary, mask outputs would rise with growing sensitivity of mask output to production technology investment effort and increasing sensitivity of mask demand to mask output.

https://www.mdpi.com/2071-1050/13/3/1115/pdf

Dynamic Adjustment Mechanism and Differential Game Model Construction of Mask Emergency Supply Chain Cooperation Based on COVID-19 Outbreak

With the development of technology, the concepts of “green” and “sustainable” have gradually been popularized in all walks of life. With the continuous development of the world mining industry, the efficiency of resource development in various countries has been improved, but mining activities and production will undoubtedly bring many environmental pollution problems. As a mining power, China is one of the first countries to put forward the concept of “green mining”. Over the years, as people emphasize safety and environmental protection, green mining technology has become the hot topic. At the same time, groundwater pollution caused by mining has become the focus of China’s “green mine construction”: with the continuous development of mining, mining activities and production will also undoubtedly bring significant environmental pollution. The environmental pollution of the mined area has a vital influence on the surrounding environment. The pollutants mainly come from mining operations and production of the mineral processing industry, including process wastewater, gas waste, smelting slag, etc., which are all acidic. Acid mine drainage (AMD) occurs in the process of mining production, due to the structure of minerals and the complex reactions between oxygen and minerals, and results in heavy metal ions leaching into groundwater. Once the groundwater is polluted, it will slowly flow to the surrounding area, resulting in the migration and diffusion of pollutants in the groundwater, affecting the surrounding rivers, farmland, and drinking water for residents. In recent years, environmental damage caused by groundwater pollution from underground mines in Shijiazhuang, China, and Selangor, Malaysia, has had a negative impact on rivers, farmland, and human health. At the same time, the paper introduces many key technologies of green mine construction, such as the backfill mining method. In cooperation with China Road & Bridge Corporation, this paper also introduces the progress in the reuse of mining waste, especially the use of mining waste as aggregate to prepare concrete materials for road and bridge construction. This information article introduces the development status of green mine construction in China and briefly reviews the key technologies of green mine construction in China.

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The Recent Progress China Has Made in Green Mine Construction, Part I: Mining Groundwater Pollution and Sustainable Mining

An entropy-cloud model is proposed to deal with soil heavy metal pollution assessment based on entropy and cloud model theory. Parameters of the cloud model of each heavy metal level are calculated with the chosen indicators, and hybrid entropy weights are determined based on Shannon entropy and the analytic hierarchy process (AHP) to generate an entropy-cloud model of all indicators. Certainty degrees of each level are calculated by the entropy-cloud model, and the fuzzy entropy of certainty degrees is calculated to indicate the complexity of heavy metal pollution. Heavy metal pollution of 10 farmland soils in mining areas is assessed by the entropy-cloud model. Comparative studies with variable fuzzy sets, artifi cial neural network, and normal cloud model show that the entropy-cloud model is effective and intuitive, which can assess the soil heavy metal pollution from two aspects of level and complexity. Different from other methods, this model provides a new way to assess soil heavy metal pollution.

http://www.pjoes.com/pdf-61883-23759?filename=Entropy_Cloud Model of.pdf

Entropy-Cloud Model of Heavy Metals Pollution Assessment in Farmland Soils of Mining Areas

In consideration of influence of loss, freshness, and secret retailer cost of products, how to handle emergency events during three-level supply chain is researched when market need is presumed to be a nonlinear function with retail price in fresh agricultural product market. Centralized and decentralized supply chain coordination models are studied based on asymmetric information. Optimal strategy of supply chain in dealing with retail price perturbation is caused by emergency events. The research reveals robustness for optimal production planning, wholesale price for distributors, wholesale price for retailers, and retail price of three-level supply chain about fresh agricultural products. The above four factors can keep constant within a certain perturbation of expectation costs for retailers because of emergency events; the conclusions are verified by numerical simulation. This paper also can be used for reference to the other related studies in how to coordinate the supply chain under asymmetric and punctual researches information response to disruptions.

/pdf/emergency-coordination-model-of-fresh-agricultural-products-zw4jl1xizw.pdf

Emergency Coordination Model of Fresh Agricultural Products’ Three-Level Supply Chain with Asymmetric Information

The production, processing, transportation, and consumption of fresh food have a significant impact on the sustainable development of the whole fresh food supply chain. There are relatively few methods and techniques to qualitatively analyze the dynamic driving factors of fresh food sustainable supply-chain management (SSCM). To solve this problem, this paper first sorts out the drivers dimensions and specific impact indicators of fresh food SSCM through the literature. Then, the integration of rough set theory and decision laboratory analysis reveals the internal strength, external connection, and comprehensive influence degree, while the prominence and relation of the driving factors are tested which reflects their priority. The results show that the competitiveness of the supply chain, food security, and strategic are the main driving factors of SSCM. Attention should be paid to green technology, product design, and green logistics. The creation and distribution of added value, as well as food security management, should be improved.

Fenghua Xiao

Papers

Entropy-Cloud Model of Heavy Metals Pollution Assessment in Farmland Soils of Mining Areas

Emergency Coordination Model of Fresh Agricultural Products’ Three-Level Supply Chain with Asymmetric Information

Identification of Key Drivers for Sustainable Supply-Chain Management of Fresh Food Based on Rough DEMATEL