The Identification for Bottleneck of Large-Scale Supply Chain Network with Random Capacity

2011 ◽  
Author(s):  
Jiyun Jiang ◽  
Hu Chen
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Supply Chain Network ◽  
Random Capacity

scholarly journals Viable Supply Chain Network Design by considering Blockchain Technology and Cryptocurrency

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Reza Lotfi ◽  
Soroush Safavi ◽  
Alireza Gharehbaghi ◽  
Sara Ghaboulian Zare ◽  
Reza Hazrati ◽  
...  
Keyword(s):  
Supply Chain ◽  
Network Design ◽  
Large Scale ◽  
Supply Chain Network Design ◽  
Supply Chain Network ◽  
Facility Locations ◽  
Blockchain Technology ◽  
Economic Justification ◽  
Main Model ◽  
Better Than

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.

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.

scholarly journals Transitional Architecture: A Temporary Architectural System for De-Industrializing Waterfronts

2021 ◽  
Author(s):  
Stephen Mauro
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Supply Chain Network ◽  
Environmental Condition ◽  
Port Cities ◽  
The Future ◽  
Post Industrial ◽  
Rail Yards

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.

scholarly journals Fuzzy Reliability Optimization for 2-Hub Center Problem with Cluster-Based Policy and Application in Cross-Border Supply Chain Network Design Using TS Algorithm

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Chenyi Yan ◽  
Xifu Wang ◽  
Kai Yang
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Reliability Optimization ◽  
Supply Chain Network ◽  
Center Problem ◽  
Fuzzy Reliability ◽  
Hub Location Problem ◽  
Cross Border

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.

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 ◽  
...  
Keyword(s):  
Supply Chain ◽  
High Resolution ◽  
Large Scale ◽  
Supply Chain Network ◽  
Biofuel Industry

scholarly journals A coevolutionary algorithm based on the auxiliary population for constrained large-scale multi-objective supply chain network

2021 ◽  
Vol 19 (1) ◽  
pp. 271-286
Author(s):  
Xin Zhang ◽  
◽  
Zhaobin Ma ◽  
Bowen Ding ◽  
Wei Fang ◽  
...  
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Complex Problem ◽  
Supply Chain Network ◽  
Multi Objective ◽  
Coevolutionary Algorithm ◽  
Two Populations ◽  
Operation Cost ◽  
Repair Operator ◽  
Operation And Management

<abstract> <p>Supply chain network is important for the enterprise to improve the operation and management, but has become more complicated to optimize in reality. With the consideration of multiple objectives and constraints, this paper proposes a constrained large-scale multi-objective supply chain network (CLMSCN) optimization model. This model is to minimize the total operation cost (including the costs of production, transportation, and inventory) and to maximize the customer satisfaction under the capacity constraints. Besides, a coevolutionary algorithm based on the auxiliary population (CAAP) is proposed, which uses two populations to solve the CLMSCN problem. One population is to solve the original complex problem, and the other population is to solve the problem without any constraints. If the infeasible solutions are generated in the first population, a linear repair operator will be used to improve the feasibility of these solutions. To validate the effectivity of the CAAP algorithm, the experiment is conducted on the randomly generated instances with three different problem scales. The results show that the CAAP algorithm can outperform other compared algorithms, especially on the large-scale instances.</p> </abstract>

scholarly journals Green design of a cellulosic butanol supply chain network: A case study of sorghum stem bio-butanol in Missouri

BioResources ◽  
2018 ◽  
Vol 13 (3) ◽  
pp. 5617-5642
Author(s):  
Li Liang ◽  
Henry J. Quesada
Keyword(s):  
Supply Chain ◽  
Large Scale ◽  
Programming Model ◽  
Biomass Energy ◽  
Green Supply Chain ◽  
Maintenance Cost ◽  
Production Plant ◽  
Scale Production ◽  
Supply Chain Network

Cellulosic butanol is a very promising renewable fuel to consider for the future transportation market. However, the seasonal availability of the raw materials, high maintenance cost, and high logistical cost of the biomass energy supply chain are the main factors impeding the commercialization and large-scale-production of this energy source. Furthermore, research focusing on an environmental or green supply chain network design of cellulosic butanol has been insufficient. This study focused on designing a green supply chain network for cellulosic butanol. A life cycle analysis was integrated into a multi-objective linear programming model to optimize the cellulosic butanol supply chain network. With the objectives of maximizing the economic profits and minimizing the greenhouse gas emissions, the proposed model can optimize the location and size of a bio-butanol production plant. The mathematical model was applied to a case study in the state of Missouri, and solved the tradeoff between the feedstock and market availabilities of sorghum stem bio-butanol.

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