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Growing Science » Authors » Behzad Masoomi

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Sort articles by: Volume | Date | Most Rates | Most Views | Reviews | Alphabet
1.

Applying fuzzy delphi and best-worst method for identifying and prioritizing key factors affecting on university-industry collaboration Pages 107-118 Right click to download the paper Download PDF

Authors: Alireza Mosayebi, Shahryar Ghorbani, Behzad Masoomi

DOI: 10.5267/j.dsl.2019.7.001

Keywords: University- Industry collaboration, Technology, Incubator, University affiliated research institutes

Abstract:
The collaboration between the universities and industries is currently in the focus of attention globally. Governments, universities, and industries are interested in good and effective collaboration, which would be beneficial for all parties. To foster University-Industry Collaboration, and to help transfer the knowledge and technology between these two parties, academics, politicians and companies are paying attention to science and technology policies more than ever. In this study, the factors affecting the improvement of University-Industry Collaboration are identified and prioritized. In the first step, 20 factors are identified and 12 factors are selected using the Fuzzy Delphi method. Then, using the BWM method, prioritizing the extracted factors is determined for industry sponsorship of the university research. Finally, based on the results, the discussion is conducted and six major strategies are presented to improve this relationship.
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Journal: DSL | Year: 2020 | Volume: 9 | Issue: 1 | Views: 1885 | Reviews: 0

 
2.

Scenario-based designing of closed-loop supply chain with uncertainty in returned products Pages 505-518 Right click to download the paper Download PDF

Authors: Iman Ghasemian Sahebi, Behzad Masoomi, Shahryar Ghorbani, Tanyeri Uslu

DOI: 10.5267/j.dsl.2019.4.003

Keywords: Closed-Loop Supply Chain, Reverse Logistics, Scenario Planning, Steel Industry

Abstract:
Closed-loop supply chain management is an effective and efficient solution for a set of activities to retrieve a product from a customer and improve its value or to dispose it. Today, designing and planning a closed-loop chain is an inevitable but difficult task. In this research, a scenario-based modeling approach is presented by considering both forward and reverse flows as a closed-loop supply chains in steel industry. The proposed study also develops a multi-product and multi-period model based on a mixed integer linear programming (MILP) approach for profit maximization. The study also considers uncertainty in the amount of raw material, processing, storage and distribution of several products flow. Uncertainty is associated with the quantity and quality of the products in the reverse flow, which are directly affected by customers and sorting centers, respectively. Finally, the model is deployed in Steel industry with real data. The results show that by increasing the quality level of returned products the need for raw materials is reduced and the total profit of the supply chain is increased.
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Journal: DSL | Year: 2019 | Volume: 8 | Issue: 4 | Views: 1585 | Reviews: 0

 

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