| 1. |
- Asadi Bagloee, Saeed, et al.
(författare)
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Tradable mobility permit with Bitcoin and Ethereum – A Blockchain application in transportation
- 2019
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Ingår i: Internet of Things (Netherlands). - : Elsevier BV. - 2542-6605. ; 8
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Tidskriftsartikel (refereegranskat)abstract
- Blockchain and its underlying technology have intrigued researchers with its promising applications and implications as “the second internet”. There is a wide range of Blockchain applications in transportation and logistics. In this paper, we present the basic principle of cryptocurrencies and Blockchain as well as Ethereum. This is followed by the potential applications of Blockchain in transportation, logistics, and supply chain industries in which the concept of a tradable mobility permit (TMP) to combat traffic congestion is formulated and numerically tested. We then discuss the deployment of the TMP scheme based on a Blockchain platform and its by-products such as dynamic toll pricing, priority for emergency vehicles, heavy truck platooning, as well as connected vehicles.
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| 2. |
- Mahmoodi, Ehsan, et al.
(författare)
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Data-driven simulation-based decision support system for resource allocation in industry 4.0 and smart manufacturing
- 2024
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Ingår i: Journal of manufacturing systems. - : Elsevier. - 0278-6125 .- 1878-6642. ; 72, s. 287-307
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Tidskriftsartikel (refereegranskat)abstract
- Data-driven simulation (DDS) is fundamental to analytical and decision-support technologies in Industry 4.0 and smart manufacturing. This study investigates the potential of DDS for resource allocation (RA) in high-mix, low-volume smart manufacturing systems with mixed automation levels. A DDS-based decision support system (DDS-DSS) is developed by incorporating two RA strategies: simulation-based bottleneck analysis (SB-BA) and simulation-based multi-objective optimization (SB-MOO). To enhance the performance of SB-MOO, a unique meta-learning mechanism featuring memory, dynamic orthogonal array, and learning rate is integrated into the NSGA-II, resulting in a modified version of the NSGA-II with meta-learning (i.e., NSGA-II-ML). The proposed DSS also benefits from a post-optimality analysis that leverages a clustering algorithm to derive actionable insights. A real-life marine engine manufacturing application study is presented to demonstrate the applicability and exhibit efficacy of the proposed DSS and NSGA-II-ML. To this aim, NSGA-II-ML was tested against the original NSGA-II and differential evolution (DE) algorithm across a set of test problems. The results revealed that NSGA-II-ML surpassed the other two in terms of the number of non-dominated solutions and hypervolume, particularly in medium and large-sized problems. Furthermore, NSGA-II-ML achieved a 24% improvement in the best throughput found in the real case problem, outperforming SB-BA, NSGA-II, and DE. The post-optimality analysis led to the extraction of valuable knowledge about the key, influencing decision variables on the throughput.
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| 3. |
- Sorooshian, Shahryar, 1980, et al.
(författare)
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From classical interpretive structural modeling to total interpretive structural modeling and beyond: A half-century of business research
- 2023
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Ingår i: Journal of Business Research. - : Elsevier BV. - 0148-2963. ; 157
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Tidskriftsartikel (refereegranskat)abstract
- Despite the widespread use of interpretive structural modeling (ISM) in business research, little is known about its overall scientific productivity and impact on business research. This study presents a comprehensive review of the published ISM research and its latest editions in business using text mining. A two-tier review (narrative and systematic) is used to examine the methods and provide a comprehensive bibliometric analysis and an application roadmap. We demonstrate the number of ISM publications has been increasing in the past fifteen years, even though ISM was developed half a century ago. The study provides evidence for the increasing impact of ISM research in business. Content analysis shows an increase in the application of an updated edition of ISM, total interpretive structural modeling (TISM). In addition, the overall scientific productivity of ISM and TISM is assessed, and an ISM/TISM method selection roadmap is proposed. We further develop ISM+, a new integrated framework combining ISM and its latest editions to improve its performance and potential applications in business research.
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| 4. |
- Tavana, Madjid, et al.
(författare)
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A novel fuzzy general best-worst method for considering diversity and inclusion in supplier selection programs
- 2024
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Ingår i: ANNALS OF OPERATIONS RESEARCH. - 0254-5330 .- 1572-9338.
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Tidskriftsartikel (refereegranskat)abstract
- Socially responsible procurement includes diversity and inclusion, and many companies have found diverse sourcing plays a substantial role in their success. Supplier diversity and inclusion initiatives can significantly impact innovation, reputation, employee engagement, and organizational retention. This paper presents a novel fuzzy general best-worst method for considering diversity and inclusion in supplier selection programs. The proposed approach considers the causal relationships between the criteria in the evaluation process within a network with complex intertwined components and a hierarchical structure. The uncertainty consideration method integrated into the proposed approach allows experts to consider ambiguous and imprecise judgments in the assessment process. We present a supplier selection case study with scenario analysis for a clean energy public-private partnership in the wind farm industry to demonstrate the applicability and efficacy of the proposed approach.
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| 5. |
- Tavana, Madjid, et al.
(författare)
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A novel fuzzy scenario-based stochastic general best-worst method
- 2024
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Ingår i: EXPERT SYSTEMS WITH APPLICATIONS. - 0957-4174 .- 1873-6793. ; 252
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Tidskriftsartikel (refereegranskat)abstract
- The best-worst method (BWM) is a popular multi-criteria decision-making (MCDM) method known for the low number of pairwise comparisons and high consistency. General BWM (GBWM) is a new version of BWM that considers the interdependencies between interwind factors in MCDM problems. This study proposes a fuzzy stochastic GBWM for weighting intertwined factors using a scenario-based approach in complex intertwined or hierarchical networks under uncertainty. Fuzzy stochastic GBWvM provides decision-makers with a wide range of weights, from fuzzy-stochastic weights to stochastic weights (defuzzified weights), fuzzy weights, and deterministic weights to use with different assumptions in the decision-making process. We demonstrate the efficacy and applicability of the proposed method with a well-known car-buying problem in the literature and a real-world problem in the transportation industry.
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| 6. |
- Tavana, Madjid, et al.
(författare)
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A systematic review of the soft computing methods shaping the future of the metaverse
- 2024
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Ingår i: Applied Soft Computing. - 1568-4946. ; 150
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Forskningsöversikt (refereegranskat)abstract
- The metaverse is an emerging technology with the potential to revolutionize our interactions with digital environments. Soft computing presents exciting opportunities in shaping this immersive virtual world. This paper provides a systematic review of the research on soft computing methods in the metaverse, highlighting the interdisciplinary nature of the field and the need for coordination to shape its future. The systematic literature review conducted in this article identifies the contributors and domains in soft computing, emphasizing the need for new developments and joint applications in soft computing and the metaverse. The study categorizes soft computing techniques into five classes - machine learning, fuzzy systems, evolutionary computing, probability analysis, and mixed/hybrid methods - contributing to the emerging metaverse-related research and development. We propose a decision framework for selecting the most suitable soft computing method to assist researchers and developers in methodically assessing the alternative methods. The findings provide a roadmap and opportunities for soft computing models and applications shaping the future of the metaverse. This article can serve as a useful reference for researchers, practitioners, and policymakers working in soft computing and the metaverse.
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| 7. |
- Tavana, Madjid, et al.
(författare)
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An integrated group fuzzy inference and best–worst method for supplier selection in intelligent circular supply chains
- 2023
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Ingår i: Annals of Operations Research. - 0254-5330 .- 1572-9338.
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Tidskriftsartikel (refereegranskat)abstract
- Circular supplier evaluation aims at selecting the most suitable suppliers with zero waste. Sustainable circular supplier selection also considers socio-economic and environmental factors in the decision process. This study proposes an integrated method for evaluating sustainable suppliers in intelligent circular supply chains using fuzzy inference and multi-criteria decision-making. In the first stage of the proposed method, supplier evaluation sub-criteria are identified and weighted from economic, social, circular, and Industry 4.0 perspectives using a fuzzy group best–worst method followed by scoring the suppliers on each criterion. In the second stage, the suppliers are ranked and selected according to an overall score determined by a fuzzy inference system. Finally, the applicability of the proposed method is demonstrated using data from a public–private partnership project at an offshore wind farm in Southeast Asia.
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