A hyper-hybrid fuzzy decision-making framework for the sustainable-resilient supplier selection problem: a case study of Malaysian Palm oil industry

Fallahpour, Alireza; Nayeri, Sina; Sheikhalishahi, Mohammad; Wong, Kuan Yew; Tian, Guangdong; Fathollahi-Fard, Amir M.

doi:10.1007/s11356-021-12491-y

Cited by 78 publications

(51 citation statements)

References 49 publications

(76 reference statements)

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“…2. The hamming-based similarity is often used for the measurement of label similarity relationships in multilabel datasets, and it demonstrates how close the label sets of x and y instances are [23][24][25]. R 𝑥 , 𝑥 is the complement of the normalized Hamming distance between the label sets of two elements.…”

Section: Phase 2 Instance-level Label Space Similarity Weightingmentioning

confidence: 99%

Unified Graph-Based Missing Label Propagation Method for Multilabel Text Classification

et al. 2022

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In multilabel classification, each sample can be allocated to multiple class labels at the same time. However, one of the prominent problems of multilabel classification is missing labels (incomplete labels) in multilabel text. The multilabel classification performance is reduced significantly with the presence of missing labels. In order to address the incomplete or missing label problem, this study proposes two methods: an aggregated feature and label graph-based missing label handling method (GB-AS), and a unified graph-based missing label propagation method (UG-MLP). GB-AS is used to obtain an initial label matrix based on the similarity of both document levels: feature-based weighting representation and label-based weighting representation. On the other hand, UG-MLP is introduced to construct a mixed graph that combines GB-AS and label correlations into a single groundwork. A high-order label correlation is learned from the incomplete training data and applied to supplement the missing label matrix, which guides the creation of multilabel classification models. The combination of the mixed graphs by UG-MLP is aimed to obtain the benefits of both graphs to increase the classification performance. To evaluate UG-MLP, the metrics of precision, recall and F-measure were used on three benchmark datasets, namely, the Reuters-21578, Bibtex and Enron datasets. The experimental results show that UG-MLP outperformed GB-AS as well as other state-of-the-art approaches. Therefore, we can infer from the findings that by plotting a unified graph based on joining aggregated feature and label weightings together with the label correlation, the performance of multilabel classification can be improved.

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Section: Phase 2 Instance-level Label Space Similarity Weightingmentioning

confidence: 99%

Unified Graph-Based Missing Label Propagation Method for Multilabel Text Classification

et al. 2022

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“…Theophilus et al (2021) studied a distribution network to optimize the truck arrivals and pickups for a case study in the Walmart company. Fallahpour et al (2021a) proposed a hybrid fuzzy programming approach for the modeling of a sustainable-resilient supply chain network. A case study of the palm oil industry in Malaysia was proposed.…”

Section: Literature Reviewmentioning

confidence: 99%

Sustainable closed-loop supply chain network under uncertainty: a response to the COVID-19 pandemic

Rafigh

Akbari

Bidhandi

et al. 2021

Environ Sci Pollut Res

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This study proposes a sustainable closed-loop supply chain under uncertainty to create a response to the COVID-19 pandemic. In this paper, a novel stochastic optimization model integrating strategic and tactical decision-making is presented for the sustainable closed-loop supply chain network design problem. This paper for the first time implements the concept of sustainable closed-loop supply chain for the application of ventilators using a stochastic optimization model. To make the problem more realistic, most of the parameters are considered to be uncertain along with the normal probability distribution. Since the proposed model is more complex than majority of previous studies, a hybrid whale optimization algorithm as an enhanced metaheuristic is proposed to solve the proposed model. The efficiency of the proposed model is tested in an Iranian medical ventilator production and distribution network in the case of the COVID-19 pandemic. The results confirm the performance of the proposed algorithm in comparison with two other similar algorithms based on different multi-objective criteria. To show the impact of sustainability dimensions and COVID-19 pandemic for our proposed model, some sensitivity analyses are done. Generally, the findings confirm the performance of the proposed sustainable closed-loop supply chain for the pandemic cases like COVID-19. Supplementary Information The online version contains supplementary material available at 10.1007/s11356-021-16077-6.

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“…, K) are requested to drawn pair-wise comparisons. In this technique, the cause-effect relationships between criteria are expressed according to linguistic words adopted from [54]. Subsequently, they translated into fuzzy numbers.…”

Section: Phase 3 Proposed Fuzzy Dematel Techniquementioning

confidence: 99%

Sustainable High-Tech Brick Production with Energy-Oriented Consumption: An Integrated Possibilistic Approach Based on Criteria Interdependencies

2021

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Brick making contributes significantly to the of supply materials for the building industry. The majority of brick production sectors, especially in developing countries, employ polluting and energy-inefficient technologies. Due to the increasing pressures on manufacturing firms to improve economic performance and growing environmental protection issues, sustainable and clean production is the main concern for brick makers. This paper considers the technological, economic, environmental, social, and energy-oriented criteria to select the optimal brick production technologies. Therefore, technology selection is viewed as a multi-criteria group decision-making (MCGDM) problem. This research proposes a novel hybrid fuzzy MCGDM (HFMCGDM) model to tackle the problem. In this respect, first of all, the modified triangular fuzzy pair-wise comparison (MTFPC) method is proposed to compute the local weights of criteria and sub-criteria. Then, a fuzzy DEMATEL (FDEMATEL) method is presented to calculate the interdependencies between and within the criteria. Moreover, the integration of MTFPC and FDEMATEL methods is applied to calculate the global criteria weights. Afterward, a novel method is proposed to determine the experts’ weight. Considering the last aggregation approach to diminish data loss, a new version of a fuzzy TOPSIS method is proposed to find the local and global priorities of the candidates. Then, a case study is given to demonstrate the applicability and superiority of the proposed methodology. To get a deeper view about considering kilns, energy and environmental performance of which has been investigated. Moreover, a comparative analysis is presented to illuminate the merits of the proposed methodology. Eventually, a sensitivity analysis is conducted to peruse the influence of criteria weights on ranking order.

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A hyper-hybrid fuzzy decision-making framework for the sustainable-resilient supplier selection problem: a case study of Malaysian Palm oil industry

Cited by 78 publications

References 49 publications

Unified Graph-Based Missing Label Propagation Method for Multilabel Text Classification

Unified Graph-Based Missing Label Propagation Method for Multilabel Text Classification

Sustainable closed-loop supply chain network under uncertainty: a response to the COVID-19 pandemic

Sustainable High-Tech Brick Production with Energy-Oriented Consumption: An Integrated Possibilistic Approach Based on Criteria Interdependencies

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