Determining a geographic high resolution supply chain network for a large scale biofuel industry

2018 ◽  
Vol 218 ◽  
pp. 266-281 ◽  
Author(s):  
Lixia He-Lambert ◽  
Burton C. English ◽  
Dayton M. Lambert ◽  
Oleg Shylo ◽  
James A. Larson ◽  
...  
2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Reza Lotfi ◽  
Soroush Safavi ◽  
Alireza Gharehbaghi ◽  
Sara Ghaboulian Zare ◽  
Reza Hazrati ◽  
...  

Nowadays, using Blockchain Technology (BCT) is growing faster in each country. It is essential to apply BCT in Supply Chain Network Design (SCND) and is considered by the designer and manager of SC. This research indicates Viable Supply Chain Network Design (VSCND) by applying BCT. A new form of two-stage robust optimization is suggested. Facility locations and activation BCT for VSCND is the first stage of decisions; finally, we determine flow transshipment between components in the next stage. The GAMS-CPLEX is used for solving the model. The results show that running BCT will decrease 0.99% in costs. There is an economic justification for using BCT when demand is high. A fix-and-optimize and Lagrange relaxation (LR) generate lower and upper bound to estimate large scale in minimum time. The gap between the main model and fix-and-optimize is better than the LR algorithm. Finally, this research suggests equipping VSCND by BCT that becomes more resilient against demand fluctuation, sustainable, and agile.


2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Hui Xia

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.


2021 ◽  
Author(s):  
Stephen Mauro

The following thesis began as an investigation into port cities that lie in the limbo between industrial and post-industrial. It questions the role of architecture during this stage of transition. The research brought forth a vision of infrastructural re-use and reversible architecture, aimed to address the indeterminate and environmental condition of de-industrialized contexts. Essentially this thesis envisions the reactivation of wasted rail and manufacturing infrastructure present among industrial-port cities. They are to become a supply chain network, producing temporary architecture. Areas of high rail density such as rail yards and industrial piers thus act as incubators of the future era; served by a reversible architecture. These communities become the focus of the city's redevelopment efforts while resisting the pressure of permanent, large scale redevelopments. As the transition from industrial to post-industrial nears stabilization, more permanent solutions will begin to emerge while the architecture may move on to serve another context.


Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Chenyi Yan ◽  
Xifu Wang ◽  
Kai Yang

As information and communication technology evolves and expands, business and markets are linked to form a complex international network, thus generating plenty of cross-border trading activities in the supply chain network. Through the observations from a typical cross-border supply chain network, this paper introduces the fuzzy reliability-oriented 2-hub center problem with cluster-based policy, which is a special case of the well-studied hub location problem (HLP). This problem differs from the classical HLP in the sense that (i) the hub-and-spoke (H&S) network is grouped into two clusters in advance based on their cross-border geographic features, and (ii) a fuzzy reliability optimization approach based on the possibility measure is developed. The proposed problem is first modeled through a mixed-integer nonlinear programming (MINLP) formulation that maximizes the reliability of the entire cross-border supply chain network. Then, some linearization techniques are implemented to derive a linear model, which can be efficiently solved by exact algorithms run by CPLEX for only small instances. To counteract the difficulty for solving the proposed problem in realistic-sized instances, a tabu search (TS) algorithm with two types of move operators (called “Swap I” and “Swap II”) is further developed. Finally, a series of numerical experiments based on the Turkish network and randomly generated large-scale datasets are set up to verify the applicability of the proposed model as well as the superiority of the TS algorithm compared to the CPLEX.


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