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Sustainable supply chain network design has attracted great attention of academia and industry in recent years. Baijiu is one of the world’s oldest distilled alcoholic beverages and plays a significant role in Chinese culture and Chinese people’s daily life. As the production and consumption of Baijiu have a significant influence on the economic, environmental, and social performance of supply chain management, sustainable supply chain network design decisions are critical to the long-term success of the industry. In concert with the rapidly growing Chinese economy, there is a growing demand for a sustainable Baijiu industry. Therefore, this paper constructs and optimizes a network decision-support model for a sustainable Baijiu industry network design. To achieve this, the Baijiu supply chain is examined and a model is proposed for a design that encompasses economic (costs), environmental (carbon emissions), and social (local employment and regional per capita GDP) dimensions. R language programming is then applied to solve the model. A case example indicated that S1 was the optimal decision for reducing costs, S2 was the optimal solution for minimizing carbon emissions, and S3 was the best for maximizing the social impact. Considering the situation of the Baijiu industry and the focal enterprise, it was concluded that S1 would be the best solution for the case company. And the results verified the effectiveness of the framework. This paper develops a systematic and effective approach that decision-makers can use to conduct sustainable network design for Baijiu enterprises. [ABSTRACT FROM AUTHOR]

Large construction and infrastructure projects are a billion-dollar business, but few studies have addressed the integrated operations in this unique domain of the construction supply chain (CSC). The comparison between the CSC and a conventional supply chain enables us to examine its framework and establish a quantitative optimization model for the CSC. To introduce the integrated operations concept into the CSC, many uncertainties need to be first dealt with, for which a multiobjective uncertain optimization model is developed. As the optimization of the owner and fabricator's costs and the service level are the main objectives, a hybrid genetic algorithm with fuzzy-random method is developed to solve the optimization model. An integrated multiobjective purchasing and production planning model is then constructed and applied to a hydropower construction project in Southwest China. The results illustrate that efficient integrated operations are critical for the CSC performance. The optimization results also indicate that considering of uncertain rush orders and delay times can be vital for optimum CSC performance. With this proposed method, construction managers can quickly respond to changing uncertain demand. This paper has highlighted that project managers need to collaborate with other stakeholders to ensure optimal CSC performance. [ABSTRACT FROM AUTHOR]

In this paper, we concentrate on dealing with a class of decision-making problems with level-2 fuzzy coefficients. We first discuss how to transform a level-2 fuzzy decision-making model with expected objectives and chance constrained into crisp equivalent models, then an interactive fuzzy satisfying method is introduced to obtain the decision makers satisfying solution. In addition, the technique of level-2 simulations is applied to deal with general level-2 fuzzy models which are usually hard to be converted into their crisp equivalents. Furthermore, based on the level-2 fuzzy programming, we focus on the supply chain network design problem where the total transport costs and the customer demands are assumed to be level-2 fuzzy numbers, a hybrid intelligent algorithm based on GA is used to solve the general supply chain design model. Finally, a numerical example and a case study are presented to illustrate the effectiveness of the model and the algorithm. [ABSTRACT FROM AUTHOR]

Continuously increasing municipal solid waste (MSW) generation, which has resulted in serious environmental pollution, resource consumption, and health problems, requires a disposal stream for improved recycling and reuse. In this study, a novel methodology is proposed that combines advanced "hard path" technologies and "soft path" policy to facilitate an effective and sustainable waste-to-energy approach. Multiple tech-economic MSW cascaded systems were established and combined for MSW terminal treatment, and a subsidy policy was applied to waste source management. Furthermore, an MSW reverse supply chain (MSWRSC) was proposed that integrates waste source and end treatment management, and a multi-objective mixed-integer dynamic model was established to optimize the MSW treatment process by achieving cost control, carbon emission reduction, and job creation. A practical case study was then conducted to provide the analysis paradigm including the system deployment and facilities operation. Further, some important conclusions and suggestions are summarized for reference by the local government and facilities. Therefore, the methodology that combines the cascade treatment systems with policy instruments shows important theoretical and pragmatic significance for the multi-dimensional sustainable development of MSW management. • Reverse supply chain is proposed for municipal solid waste treatment. • Dynamic planning is employed to address uncertainties in waste management. • Advanced cascaded systems are established and combined for targeted waste treatment. • Sorting subsidy is validly applied and examined towards waste management. • Equilibrium optimization between economy, environment and society is achieved. [ABSTRACT FROM AUTHOR]

The evaluation of supply chain (SC) alliances in a bidding environment has received increasing attention in today’s business environment. This study focuses on developing an evaluation tool to provide an improved method for assuring optimal alliance selection and efficient supply chain management (SCM) using a fuzzy Delphi method and fuzzy analytic hierarchy process and demonstrates how this can be extended from supplier selection to an alliance environment. The main contributions of this paper are the development of an interactive evaluation process for SC alliance in a bidding environment by introducing novel aspects such as a synthetic measurement index and a user-friendly platform. On this platform, the distributed users can work collaboratively using the Internet. Specifically, this paper develops a relatively stable system that employs a supply chain operations reference and a computer-integrated web-based platform (CIWBP) to support implementation. The efficiency and practical implication of the CIWBP are validated with a real-life case study. The developed system assists in the making of reasonable choices and identifies performance improvement objectives, all of which have the possibility of positively influencing future SCM development and assisting a bulk purchase manager in making better decisions. This proposed system could easily be extended to more complex real-world applications. [ABSTRACT FROM AUTHOR]

The significant rise in greenhouse gas (GHG) and acidifying gas (AG) emissions have resulted in serious global warming and acidification problems, a major source of which are the emissions from construction materials. To reduce these adverse effects, it is vital that the overall environmental performances of construction materials supply chain networks (CMSCN) be evaluated and optimized. To this end, to fully consider the GHG and AG emissions, control total CMSCN costs, and determine a reasonable trade-off between economic development and environmental protection, this paper developed an innovative environmental evaluation method (EEM) nested in a multi-objective optimization model. The proposed approach was then applied to a practical case study in China to demonstrate its efficiency and effectiveness in controlling GHG greenhouse and AG acidification problems and mitigating ecological-economic conflicts. Scenario analyses were also conducted focused on cost control and problem attention ratios, after which some targeted conclusions and policy suggestions were given. By comprehensively considering both the environmental effects and the economic benefits, the proposed methodology was shown to efficiently control GHG and AG emissions, reduce costs, and provide practical guidance on the sustainable development of CMSCN. [ABSTRACT FROM AUTHOR]