An intuitive fuzzy approach for evaluating financial resiliency of supply chain

Taşkin

et al. 2022

Information

Self Cite

Supply chains have received significant attention in recent years. Neural networks (NN) are a technique available in artificial intelligence (AI) which has many supporters due to their diverse applications because they can be used to move towards complete harmony. NN, an emerging AI technique, have a strong appeal for a wide range of applications to overcome many issues associated with supply chains. This study aims to provide a comprehensive view of NN applications in supply chain management (SCM), working as a reference for future research directions for SCM researchers and application insight for SCM practitioners. This study generally introduces NNs and has explained the use of this method in five features identified by supply chain area, including optimization, forecasting, modeling and simulation, clustering, decision support, and the possibility of using NNs in supply chain management. The results showed that NN applications in SCM were still in a developmental stage since there were not enough high-yielding authors to form a strong group force in the research of NN applications in SCM.

Section: Methodsmentioning

confidence: 99%

Reviewing the Applications of Neural Networks in Supply Chain: Exploring Research Propositions for Future Directions

Taşkin

et al. 2022

Information

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“…In recent years, many researchers have focused on the field of supply chains [9,18,32]. The purpose of anyone active in the supply chain is to increase competitiveness or increase customer service [33]. The supply chain considers all the organizations involved [32][33][34].…”

Section: Model Formulationmentioning

confidence: 99%

“…The purpose of anyone active in the supply chain is to increase competitiveness or increase customer service [33]. The supply chain considers all the organizations involved [32][33][34]. This shows the effect of cost and time on customer satisfaction.…”

Section: Model Formulationmentioning

confidence: 99%

The Design of a Multi-Period and Multi-Echelon Perishable Goods Supply Network under Uncertainty

Yıldırım

et al. 2022

Sustainability

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The value of superior supply network design is becoming increasingly important, especially in the perishable supply chain. Due to the recent developments in perishable products, perishable product supply chain (PPSC) management has attracted many researchers. The purpose of this study was to present a multi-period and multi-echelon perishable supply chain with regards to procurement time, cycle cost, and customer satisfaction. This study presented a new form of location-routing in a supply chain network for perishable products, accounting for environmental considerations, cost, procurement time, and customer satisfaction, such that the total costs, delivery time, and the emission of pollutants in the network were minimized while customer satisfaction was maximized. We formulated the problem as a multi-objective, nonlinear, mixed-integer program and the hybrid approach was proposed to solve the model. The mean error of the proposed algorithm for the objective function compared to the exact method in solving the sample problems was less than 3.4%. The computational results revealed the efficiency of the proposed algorithm for a wide range of issues of various sizes.

“…Still, the theory of gray does not operate based on the available information range. According to the above, a gray number is a number whose exact value is unknown, but the field in which it is located is specified [67]. In general, the inclusion of gray theory over fuzzy conditions and its flexibility in dealing with issues is uncertain.…”

Section: Gray Dematelmentioning

confidence: 99%

An Integrated Approach for Evaluating Lean Innovation Practices in the Pharmaceutical Supply Chain

Cebeci

et al. 2021

Logistics

Self Cite

Backgroung: Lean innovation focuses on minimizing waste in the product development stages in order to increase productivity by obtaining customer feedback more quickly and efficiently. The usage of lean innovation practices in product development stages in the pharmaceutical supply chain is the topic of an increasing amount of research on the critical question of how lean innovation practices can be implemented in a pharmaceutical supply chain or logistic sector. To answer this question, we first identified lean innovation practices by reviewing the literature. Methods: the identified practices were screened using the fuzzy Delphi method (FDM). The expert panel included eight persons working in pharmaceutical supply chain fields. In the next step, the causal relationships between practices were analyzed using the Gray DEMATEL (GDEMATEL) technique. Results: show that technological knowledge was the most crucial factor in lean innovation practices in the pharmaceutical supply chain. Conclusions: Actualizing lean innovation in the supply chain is more than just utilizing the correct strategies and instruments. To execute lean innovation effectively, a reevaluation must be accomplished: A culture that recognizes requirements for change and is set up for consistent change is essential. Methodological strategies such as the value system cannot be set up as a one-time strategy. To execute lean innovation on a long-haul premise, members must be included and become acclimated to a proceeding with the progress process. Changes in forms are frequently used because of an absence of association of suppliers, regardless of whether measures are sensible.