Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method

Tian, Guangdong; Zhang, Honghao; Feng, Ying; Wang, Danqi; Peng, Yong; Jia, Hongfei

doi:10.1016/j.rser.2017.08.050

Cited by 230 publications

(82 citation statements)

References 85 publications

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“…the MCDM problem [38], that is evaluating the design alternatives by the gray relational closeness index (R) among data sequences as a measurement scale through analyzing similarity curve geometry and geometric relations among data sequences [27,28]. Note that the closer the curve, the larger the R. The detailed procedures could be summarized as follows:…”

Section: Gra Methods Gra Methods Was Proposed To Solvementioning

confidence: 99%

“…An overview of main methodologies for solving this problem by former researchers is revealed briefly in this section. Some MCDM methods, e.g., AHP, analytic network process (ANP), GRA, the technique for order preference by similarity to ideal solution (TOPSIS), and Decision-Making and Evaluation Laboratory (DEMATEL) and integrated approaches, e.g., gray-based DEMATEL and GC-TOPSIS, have been successfully presented and utilized to solve the GSCM problem [3,13,[25][26][27][28][29][30][31].…”

Section: Introductionmentioning

confidence: 99%

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Green supply chain management of automotive manufacturing industry considering multiperspective indices

Huang

Zhang

2019

IEEJ Transactions Elec Engng

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Considering strategic targets and fierce competition, high‐efficiency supply chain management (SCM) and selection strategy has a significant impact on the automotive manufacturing industry to improve its competitive advantage and economic benefit. However, the selection process of supply chain is often inevitably affected by multiperspective factors, e.g., societal and economic properties. Thus, multicriteria decision‐making as an effective method is needed. This article establishes a systematic hierarchical structure of multiperspective indices for SCM of automotive manufacturing industry including economic, environmental, societal, and technical properties. An integrated method that combines gray relational analysis and analytic hierarchy process is applied to select the optimal pattern of supply chain. An empirical case about three types of supply chain for automotive manufacturing industry is applied to test the effectiveness of multicriteria decision‐making method and the hierarchical structure. In addition, a comparison with other methods and a sensitivity analysis are conducted to validate the reliability of this research. The results show this method can be effectively used in the decision‐making process of SCM in the automotive manufacturing industry. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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Section: Gra Methods Gra Methods Was Proposed To Solvementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Green supply chain management of automotive manufacturing industry considering multiperspective indices

Huang

Zhang

2019

IEEJ Transactions Elec Engng

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“…In recent years, Anojkumar et al [31] used fuzzy AHP (Analytic Hierarchy Process), VIKOR and TOPSIS for MSP in the sugar industry. Furthermore, interval type 2 fuzzy TOPSIS [4], Multi-Attributive Border Approximation area Comparison [7] (MABAC), hybrid MCDM framework with DEMATEL, ANP and TOPSIS models [18], neutrosophic MULTIMOORA [32], and grey-correlation-based hybrid MCDM method [33] are notable contributions in MSP in recent times. All the authors except Xue et al [7] have used either fuzzy sets or crisp sets.…”

Section: Msp and Various Mcdmsmentioning

confidence: 99%

An Extension of the CODAS Approach Using Interval-Valued Intuitionistic Fuzzy Set for Sustainable Material Selection in Construction Projects with Incomplete Weight Information

et al. 2019

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Optimal selection of sustainable materials in construction projects can benefit several stakeholders in their respective industries with the triple bottom line (TBL) framework in a broader perspective of greater business value. Multiple criteria of social, environmental, and economic aspects should be essentially accounted for the optimal selection of materials involving the significant group of experts to avoid project failures. This paper proposes an evaluation framework for solving multi criteria decision making (MCDM) problems with incomplete weight information by extending the combinative distance assessment (CODAS) method with interval-valued intuitionistic fuzzy numbers. To compute the unknown weights of the evaluation criteria, this paper presents an optimization model based on the interval-valued intuitionistic fuzzy distance measure. In this study, we emphasize the importance of individual decision makers. To illustrate the proposed approach, an example of material selection in automotive parts industry is presented followed by a real case study of brick selection in sustainable building construction projects. The comparative study indicates the advantages of the proposed approach in comparison with the some relevant approaches. A sensitivity analysis of the proposed IVIF-CODAS method has been performed by changing the criteria weights, where the results show a high degree of stability.

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“…Thus, the recycling and remanufacture of mechanical equipment have become priorities to be considered by industry [1][2][3][4]. Recently, researchers have started to focus on design and decision-making for recycling [5][6][7][8][9]. Disassembly, as a key step of recycling and remanufacturing, has also attracted wide attention.…”

Section: Introductionmentioning

confidence: 99%

Sequence Planning for Selective Disassembly Aiming at Reducing Energy Consumption Using a Constraints Relation Graph and Improved Ant Colony Optimization Algorithm

Feng

Zheng

et al. 2018

Energies

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With environmental pollution and the shortage of resources becoming increasingly serious, the disassembly of certain component in mechanical products for reuse and recycling has received more attention. However, how to model a complex mechanical product accurately and simply, and minimize the number of components involved in the disassembly process remain unsolved problems. The identification of subassembly can reduce energy consumption, but the process is recursive and may change the number of components to be disassembled. In this paper, a method aiming at reducing the energy consumption based on the constraints relation graph (CRG) and the improved ant colony optimization algorithm (IACO) is proposed to find the optimal disassembly sequence. Using the CRG, the subassembly is identified and the number of components that need to be disassembled is minimized. Subsequently, the optimal disassembly sequence can be planned using IACO where a new pheromone factor is proposed to improve the convergence performance of the ant colony algorithm. Furthermore, a case study is presented to illustrate the effectiveness of the proposed method.

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Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method

Cited by 230 publications

References 85 publications

Green supply chain management of automotive manufacturing industry considering multiperspective indices

Green supply chain management of automotive manufacturing industry considering multiperspective indices

An Extension of the CODAS Approach Using Interval-Valued Intuitionistic Fuzzy Set for Sustainable Material Selection in Construction Projects with Incomplete Weight Information

Sequence Planning for Selective Disassembly Aiming at Reducing Energy Consumption Using a Constraints Relation Graph and Improved Ant Colony Optimization Algorithm

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