scholarly journals A Privacy Preserving Approach to Collaborative Systemic Risk Identification: The Use-Case of Supply Chain Networks

2018 ◽  
Vol 2018 ◽  
pp. 1-18
Author(s):  
Tirazheh Zare-Garizy ◽  
Gilbert Fridgen ◽  
Lars Wederhake
Keyword(s):  
Supply Chain ◽  
Structural Information ◽  
Risk Identification ◽  
Use Case ◽  
Supply Chain Network ◽  
Strategic Positioning ◽  
Supply Chain Networks ◽  
Structural Risk ◽  
Main Factors ◽  
Network Risk

Globalization and outsourcing are two main factors which are leading to higher complexity of supply chain networks. Due to the strategic importance of having a sustainable network, it is necessary to have an enhanced supply chain network risk management. In a supply chain network many firms depend directly or indirectly on a specific supplier. In this regard, unknown risks of network’s structure can endanger the whole supply chain network’s robustness. In spite of the importance of risk identification of supply chain network, firms are not willing to exchange the structural information of their network. Firms are concerned about risking their strategic positioning or established connections in the network. The paper proposes to combine secure multiparty computation cryptography methods with risk identification algorithms from social network analysis to address this challenge. The combination enables structural risk identification of supply chain networks without endangering firms’ competitive advantage.

scholarly journals Mathematical modeling for optimizing the blood supply chain network

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Amir Rahimzadeh Dehaghani ◽  
Muhammad Nawaz ◽  
Rohullah Sultanie ◽  
Tawiah Kwatekwei Quartey-Papafio
Keyword(s):  
Supply Chain ◽  
Blood Supply ◽  
Supply Chain Network ◽  
Distribution Centers ◽  
Nsga Ii ◽  
Content Type ◽  
Supply Chain Networks ◽  
Multi Objective ◽  
Blood Supply Chain ◽  
The Cost

PurposeThis research studies a location-allocation problem considering the m/m/m/k queue model in the blood supply chain network. This supply chain includes three levels of suppliers or donors, main blood centers (laboratories for separation, storage and distribution centers) and demand centers (hospitals and private clinics). Moreover, the proposed model is a multi-objective model including minimizing the total cost of the blood supply chain (the cost of unmet demand and inventory spoilage, the cost of transport between collection centers and the main centers of blood), minimizing the waiting time of donors in blood donating mobile centers, and minimizing the establishment of mobile centers in potential places.Design/methodology/approachSince the problem is multi-objective and NP-Hard, the heuristic algorithm NSGA-II is proposed for Pareto solutions and then the estimation of the parameters of the algorithm is described using the design of experiments. According to the review of the previous research, there are a few pieces of research in the blood supply chain in the field of design queue models and there were few works that tried to use these concepts for designing the blood supply chain networks. Also, in former research, the uncertainty in the number of donors, and also the importance of blood donors has not been considered.FindingsA novel mathematical model guided by the theory of linear programming has been proposed that can help health-care administrators in optimizing the blood supply chain networks.Originality/valueBy building upon solid literature and theory, the current study proposes a novel model for improving the supply chain of blood.

Evolutionary Game Model of Information Sharing Behavior in Supply Chain Network With Agent-Based Simulation

2019 ◽  
Vol 15 (2) ◽  
pp. 54-68 ◽  
Author(s):  
Jian Tan ◽  
Guoqiang Jiang ◽  
Zuogong Wang
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Evolutionary Game ◽  
Supply Chain Network ◽  
Agent Based Simulation ◽  
Control Cost ◽  
Agent Based ◽  
Supply Chain Networks ◽  
Network Information ◽  
Sharing Behavior

In the supply chain network, information sharing between enterprises can produce synergistic effect and improve the benefits. In this article, evolutionary game theory is used to analyse the evolution process of the information sharing behaviour between supply chain network enterprises with different penalties and information sharing risk costs. Analysis and agent-based simulation results show that when the amount of information between enterprises in supply chain networks is very large, it is difficult to form a sharing of cooperation; increase penalties, control cost sharing risk can increase the probability of supply chain information sharing network and shorten the time for information sharing.

Use Of Genetic Algorithms in Supply Chain Management. Literature Review and Current Trends

2013 ◽  
Vol 27 (1) ◽  
pp. 0-0
Author(s):  
Piotr Stawiński
Keyword(s):  
Supply Chain ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Design Problems ◽  
Research And Practice ◽  
Supply Chain Networks ◽  
The Past ◽  
Current Trends ◽  
Management Literature ◽  
The Subject

For the past few decades SCM has been one of the main objectives in research and practice. Since that time researchers have developed a lot of methods and procedures which optimized this process. To create an efficient supply chain network the resources and factories must be tightly integrated. The most supply chain network designs have multiple layers, members, periods, products, and comparative resources constraints exist between different layers. Supply chain networks design is related to the problems which are very popular in literature. The subject of this paper is to present the variants, configurations and parameters of genetic algorithm (GA) for solving supply chain network design problems. We focus on references from 2000 to 2011. Furthermore, current trends are introduced and discussed.

An incentive mechanism-based negotiation model for green supply chain networks

2020 ◽  
pp. 014233122092981
Author(s):  
Fang Yu ◽  
Chun Zhang ◽  
Yongsheng Yang
Keyword(s):  
Carbon Dioxide ◽  
Supply Chain ◽  
Carbon Dioxide Emissions ◽  
Green Supply Chain ◽  
Supply Chain Network ◽  
Supply Chain Networks ◽  
Environmental Attributes ◽  
Proposed Model ◽  
Total Profit ◽  
Negotiation Mechanism

This research aims to prompt agents to improve their strategies initiatively in order to decrease carbon dioxide emissions and enhance green factors during production and consumption processes. An incentive negotiation mechanism is proposed for agents in supply chains to improve their strategies. Multiple items, multiple attributes, and multiple echelons are involved in the proposed model. In addition, this research takes both the commerce and the environmental attributes into account. The environmental attributes were transformed into rewards or penalty by setting reward factors or penalty factors, and were taken into account during the calculation of the profits. The simulation results show that the proposed model was feasible to solve the complex negotiation problems, and had a good performance. The green factors of agents in the green supply chain network are increased when the agents have low initial green factors. Moreover, the proposed model can effectively reduce the carbon dioxide emissions as well. The proposed model can be seen as a “win–win” solution from the perspective of both business and environmental protection. The total profit of the green supply chain network is improved, and the harm to the environment is decreased as well.

scholarly journals Rewiring Strategy Based on Directed Betweenness to Mitigate Disruptions of Large-Scale Supply Chain Networks

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Hui Xia
Keyword(s):  
Supply Chain ◽  
Empirical Data ◽  
Large Scale ◽  
Network Connectivity ◽  
The Other ◽  
Network Robustness ◽  
Data Driven ◽  
Supply Chain Network ◽  
Supply Chain Networks ◽  
The Impact

In current large-scale supply chain networks, unexpected disruptions degrade the supply availability and network connectivity for modern enterprises. How to improve the robustness of supply chain networks is very important for modern enterprises. In this paper, we explore how to improve the robustness of supply chain networks from a topological perspective. Firstly, through the empirical data-driven study, we show that the directed betweenness metric is more suitable than the other topological metrics in evaluating the robustness of supply chain networks. Then, we propose a rewiring algorithm based on directed betweenness to improve network robustness under the impact of disruptions. The experimental results in the large-scale supply chain network show that the rewiring algorithm based on directed betweenness effectively improves the network robustness.

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