Green supplier selection and order allocation in a low-carbon paper industry: integrated multi-criteria heterogeneous decision-making and multi-objective linear programming approaches

With a great emphasis on both social and environmental responsibilities, sustainable supply chain management has gradually been adopted and promoted as an innovative business model. In sustainable supply chain practice, the choice of sustainable suppliers relates to the long-term development of a company. While the environmental performance of suppliers has been commonly considered, the social dimension has not yet received enough attention. This paper first proposes a novel criteria system for evaluating sustainable suppliers from three aspects and six dimensions, and then introduces an integrated evaluation model with a novel hybrid information aggregation. To verify the applicability and effectiveness of the proposed method, a real case of a large supermarket is introduced and analyzed. The research results show that (1) the indicator system based on Triple Bottom Line theory can serve as a framework of sustainable supplier selection for manufacturing and circulation enterprises; (2) the introduction of hybrid information aggregation can effectively handle the uncertainties of indicator scores under the realistic fuzzy environment and objectively reflect the intentions of the scorers; and (3) in comparison with the TOPSIS algorithm, the priority order finally obtained is consistent, but the proposed model shows more robustness in the sensitivity test.

Section: Implications and Discussionsupporting

confidence: 61%

An Integrated Sustainable Supplier Selection Approach Based on Hybrid Information Aggregation

Zhou

Zhang

2018

“…The fuzzy approach is proposed for evaluating environmental performance of suppliers and supporting the selection of the best green suppliers [71,78,80,142]. For example, Govindan et al (2013) [27] identify a fuzzy model based on triple bottom line approach for supplier selection operations.…”

Section: Cluster 4: Modeling Methods For Green Supplier Selection Of Gsmentioning

confidence: 99%

Sustainable Global Sourcing: A Systematic Literature Review and Bibliometric Analysis

Jia

Yan

2018

Sustainable Global Sourcing (SGS) is a rapidly emerging field with a geometric growth that is evidenced by the number of articles published within this field. The aim of this paper is to develop a systematic study quantitatively depicting the knowledge structure of the SGS field. A bibliometric analysis in conjunction with citation analysis and co-citation analysis is adopted to evaluate a total of 287 journal articles identified from systematic selection of influential work. A further content analysis is performed to obtain the detailed insights on the results of bibliometric analysis. Findings show five research clusters that constitute the SGS field, i.e., (i) Global Sourcing (GS) practice and environmental performance; (ii) Social sustainability/ethical sourcing practice in GS; (iii) Environmental evaluation criteria and certification; (iv) Fuzzy modelling of environmental practice in GS; (v) Effects of environmental and social sustainability practice on economic performance. On this basis, eight research directions are outlined for future research. This study provides an innovative method for systematic literature review work and robust indications for future investigations in the SGS field.

“…Until now, many methods have been utilized to solve the MODM problems [31][32][33][34]. For example, Zhang et al [31] study the city sustainability evaluation problem by using objective weights approach; Govindan and Sivakumar [32] propose a fuzzy Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method to solve the multi-objective linear programming method in green and low-carbon development; Gutjahr and Pichler [33] use non-scalarizing methods to optimize stochastic multi-objective decision making; Delgoda et al [34] design a novel generic optimization method for irrigation scheduling under multiple objectives; Deng et al [35] propose an improved APSO algorithm to solve the multi-objective optimization model. In particular, MODM [36] and multi-criteria [37] have been used to assess people's life and environment for sustainable urbanization.…”

Section: Modm Methodsmentioning

confidence: 99%

Gathered Village Location Optimization for Chinese Sustainable Urbanization Using an Integrated MODM Approach under Bi-Uncertain Environment

Lu¹,

Wang²,

Hu³

2017

Urbanization has become a main challenge all over developing countries in the 21st Century. However, decision making should take into account the different national situations with their complex factors to achieve sustainable development. As standards of living have risen in urban areas, local/neighbor urbanization has become a coming trend in China. With this in mind, the paper focuses on the optimization of nearby gathered village locations in Population Migration (PM) with consideration of both qualitative and quantitative criteria. Therefore, an integrated multiple objective decision making approach (MODM) under a bi-uncertain environment is proposed to solve this problem, which is based on the comprehensive Economy-Society-Ecology-Resource-Religion (ESERR) urbanization concept. The first step is to establish a bi-uncertain multiple objective programming model orienting the problem. Secondly, the model process is composed of fuzzy random variable transformation and the expected value model based on a new fuzzy measure, which is given accordingly to obtain the equivalent model. Thirdly, in order to describe the model efficiently, the Multi-Objective Adaptive Global Local Neighbor Particle Swarm Optimization (MOAGLNPSO) with three-dimensional Pareto optimal judgment criteria is designed. Finally, a case study is tested to validate the effectiveness and to illustrate the advantages of the whole approach. This novel approach can help optimize sustainable urbanization strategies and ensure their realistic application.