A survey of multi-criteria decision-making techniques for green logistics and low-carbon transportation systems

Tian, Guangdong; Lu, Weidong; Zhang, Xuesong; Zhan, Meng; Dulebenets, Maxim A.; Александров, А.А.; Fathollahi-Fard, Amir M.; Ivanov, Mikhail

doi:10.1007/s11356-023-26577-2

Cited by 79 publications

(28 citation statements)

References 184 publications

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“…In conclusion, prior research has demonstrated that AHP and fuzzy AHP are multi-criteria decision-making methods that can be applied effectively to various higher education objectives [37,38]. Fuzzy AHP methods offer a methodical and objective approach to evaluating and comparing alternative options based on multiple criteria [39]. Several studies have found that fuzzy AHP is more adept than AHP at handling uncertain and ambiguous criteria and alternatives [40].…”

Section: Introductionmentioning

confidence: 89%

Dynamic Multi-Criteria Decision Making of Graduate Admission Recommender System: AHP and Fuzzy AHP Approaches

2023

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The optimal management of personal resources impacts everyone’s quality of life. An investment in graduate education is a sustainable opportunity for improved outcomes in human life, including cognition, behavior, life opportunities, salary, and career. Advanced technology dramatically reduces the risk of personal resources in graduate program admission recommendations that depend on multiple individual needs and preferences. In the digital age, a dynamic recommender system enhances the suitably effective solution for students’ university selections. This study focused on designing, developing, and testing a recommender system for graduate admission using a dynamic multi-criteria AHP and fuzzy AHP approach. The explicit multi-criteria recommender system was a platform as a service (PaaS) web application created to aid in graduate admissions management and decision-making. The design proposed that the bit representation store a dynamic explicit multi-criteria data structure. The recommendations adopting dynamic multi-criteria were validated by comparing them to the programs to which the students were actually admitted and enrolled. They individually ranked the evaluation outcomes of dynamic explicit multi-criteria and alternative preferences to provide graduate admission recommendations. Eighty graduate students in information technology evaluated the recommender system. Using top-1, top-2, and F1-score accuracy, the effective system accuracy performance on the dynamic multi-criteria recommender system was evaluated using AHP and fuzzy AHP approaches. The fuzzy AHP demonstrated marginally greater practical accuracy than the AHP method.

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Section: Introductionmentioning

confidence: 89%

Dynamic Multi-Criteria Decision Making of Graduate Admission Recommender System: AHP and Fuzzy AHP Approaches

2023

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“…After conducting a careful analysis of the literature, as well as on-site research, this study aimed to identify and screen the factors that affect the development of low-carbon transportation. To achieve this, a comprehensive review of the literature (Tian et al 2023a ; Cui et al 2018 ; Xu et al 2017 ; Tian et al 2022a , b ) was conducted, which provided a solid basis for the subsequent analysis. In the next stage, the factors affecting the development of low-carbon transportation were identified and screened.…”

Section: Identification Of Criteriamentioning

confidence: 99%

“…With the continuous development of the social economy and technology, research on supply chains, logistics, and transportation has become increasingly active. However, energy consumption, carbon emissions, and environmental pollution resulting from these activities remain significant concerns (Wen et al 2022 ; Tian et al 2023a ; Du et al 2023 ; Moslem et al 2019 ). The promotion of green logistics development has become a grand challenge for both developed and developing countries (Moslem et al 2019 ; Awasthi et al 2011 ).…”

Section: Introductionmentioning

confidence: 99%

“…While the transportation industry in China is undergoing a significant shift from old to new energy sources, the vigorous development of new energy power can reduce some environmental pollution. However, the inability of the long-distance transportation industry to achieve a breakthrough still inevitably leads to a series of environmental problems (Tian et al 2023a ).…”

Section: Introductionmentioning

confidence: 99%

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A hybrid approach for low-carbon transportation system analysis: integrating CRITIC-DEMATEL and deep learning features

Zhan¹,

Yuan²,

Chen³

et al. 2023

Int. J. Environ. Sci. Technol.

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As supply chains, logistics, and transportation activities continue to play a significant role in China's economic and social developments, concerns around energy consumption and carbon emissions are becoming increasingly prevalent. In light of sustainable development goals and the trend toward sustainable or green transportation, there is a need to minimize the environmental impact of these activities. To address this need, the government of China has made efforts to promote low-carbon transportation systems. This study aims to assess the development of low-carbon transportation systems in a case study in China using a hybrid approach based on the Criteria Importance Through Intercriteria Correlation (CRITIC), Decision-Making Trial and Evaluation Laboratory (DEMATEL) and deep learning features. The proposed method provides an accurate quantitative assessment of low-carbon transportation development levels, identifies the key influencing factors, and sorts out the inner connection among the factors. The CRITIC weight matrix is used to obtain the weight ratio, reducing the subjective color of the DEMATEL method. The weighting results are then corrected using an artificial neural network to make the weighting more accurate and objective. To validate our hybrid method, a numerical example in China is applied, and sensitivity analysis is conducted to show the impact of our main parameters and analyze the efficiency of our hybrid method. Overall, the proposed approach offers a novel method for assessing low-carbon transportation development and identifying key factors in China. The results of this study can be used to inform policy and decision-making to promote sustainable transportation systems in China and beyond.

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“…With the increasing severity of environmental problems, low-carbon development has become an inevitable choice [1]. There are many resources wasted in multi-variety and small batch aerospace enterprises; complex aerospace components are mixed with small batches, complex geometric features and changeable process routes, which lead to poor matching between processing features and manufacturing resources, and then make production lines switch frequently, resulting in low production efficiency, making it difficult to meet the dynamic and changeable model requirements [2][3][4][5].…”

Section: Introductionmentioning

confidence: 99%

Integrated Optimization of Process Planning and Scheduling for Aerospace Complex Component Based on Honey-Bee Mating Algorithm

et al. 2023

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To cope with the problems of poor matching between processing characteristics and manufacturing resources, low production efficiency, and the hard-to-meet dynamic and changeable model requirements in multi-variety and small batch aerospace enterprises, an integrated optimization method of complex component process planning and workshop scheduling for aerospace manufacturing enterprises is proposed. This paper considers the process flexibility of aerospace complex components comprehensively, and an integrated optimization model for the process planning and production scheduling of aerospace complex components is established with the optimization objectives of achieving a minimum makespan, machining time and machining cost. A honey-bee mating optimization algorithm (HBMO) combined with the greedy algorithm was proposed to solve the model. Then, it formulated a four-layer encoding method based on a feature-processing sequence, processing method, and machine tool, a tool was designed, and five worker bee cultivation strategies were designed to effectively solve the problems of infeasible solutions and local optimization when a queen bee mated to a drone. Finally, taking the complex component parts of an aerospace enterprise as an example, the integrated optimization of process planning and workshop scheduling is carried out. The results demonstrate that the proposed model and algorithm can effectively shorten the makespan and machining time, and reduce the machining cost.

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A survey of multi-criteria decision-making techniques for green logistics and low-carbon transportation systems

Cited by 79 publications

References 184 publications

Dynamic Multi-Criteria Decision Making of Graduate Admission Recommender System: AHP and Fuzzy AHP Approaches

Dynamic Multi-Criteria Decision Making of Graduate Admission Recommender System: AHP and Fuzzy AHP Approaches

A hybrid approach for low-carbon transportation system analysis: integrating CRITIC-DEMATEL and deep learning features

Integrated Optimization of Process Planning and Scheduling for Aerospace Complex Component Based on Honey-Bee Mating Algorithm

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