scholarly journals A Stochastic Optimization Model for Carbon Mitigation Path under Demand Uncertainty of the Power Sector in Shenzhen, China

2017 ◽  
Vol 9 (11) ◽  
pp. 1942
Author(s):  
Guangxiao Hu ◽  
Xiaoming Ma ◽  
Junping Ji
Keyword(s):  
Stochastic Optimization ◽  
Optimization Model ◽  
Demand Uncertainty ◽  
Carbon Mitigation ◽  
Power Sector

Stochastic optimization of economic, financial, information, and logistics inter-cluster cooperation

2020 ◽  
Vol 26 (9) ◽  
pp. 1928-1950
Author(s):  
S.N. Yashin ◽  
Yu.V. Trifonov ◽  
E.V. Koshelev
Keyword(s):  
Public Policy ◽  
Population Growth ◽  
Stochastic Optimization ◽  
Optimization Model ◽  
Federal District ◽  
Industrial Clusters ◽  
Financial Information ◽  
Policy Management ◽  
Federal Districts ◽  
Further Development

Subject. This article deals with the simulation technologies based on the principles of stochastic optimization. They can bring a significant financial effect in the planning of investment development of both individual innovation and industrial clusters and federal districts of the country. Objectives. The article aims to investigate the mechanisms of inter-cluster cooperation within a single district. Methods. For the analysis, we used a stochastic optimization model in view of economic, financial, information, and logistics inter-cluster cooperation within a single federal district. Results. The considered stochastic optimization model of economic, financial, information, and logistics inter-cluster cooperation shows that the increase in fixed investment does not always cause population growth in the federal district regions. Conclusions. The use of a digital twin mechanism of inter-cluster cooperation can help avoid premature unreasonable public policy management decisions regarding the further development of innovation and industrial clusters.

Design of hydrogen supply chains under demand uncertainty – a case study of passenger transport in Germany

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Anton Ochoa Bique ◽  
Leonardo K. K. Maia ◽  
Ignacio E. Grossmann ◽  
Edwin Zondervan
Keyword(s):  
Stochastic Optimization ◽  
Demand Uncertainty ◽  
Programming Model ◽  
Cost Minimization ◽  
Water Electrolysis ◽  
Scenario Tree ◽  
Mixed Integer ◽  
Optimization Approach ◽  
Strong Impact ◽  
Hydrogen Supply

Abstract A strategy for the design of a hydrogen supply chain (HSC) network in Germany incorporating the uncertainty in the hydrogen demand is proposed. Based on univariate sensitivity analysis, uncertainty in hydrogen demand has a very strong impact on the overall system costs. Therefore we consider a scenario tree for a stochastic mixed integer linear programming model that incorporates the uncertainty in the hydrogen demand. The model consists of two configurations, which are analyzed and compared to each other according to production types: water electrolysis versus steam methane reforming. Each configuration has a cost minimization target. The concept of value of stochastic solution (VSS) is used to evaluate the stochastic optimization results and compare them to their deterministic counterpart. The VSS of each configuration shows significant benefits of a stochastic optimization approach for the model presented in this study, corresponding up to 26% of infrastructure investments savings.

scholarly journals A three-stage stochastic optimization model for the Brazilian biodiesel supply chain

Production ◽  
2016 ◽  
Vol 26 (3) ◽  
pp. 501-515 ◽  
Author(s):  
Pedro Senna ◽  
Denis Pinha ◽  
Rashpal Ahluwalia ◽  
Julio Cesar Guimarães ◽  
Eliana Severo ◽  
...  
Keyword(s):  
Supply Chain ◽  
Stochastic Optimization ◽  
Optimization Model
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