scholarly journals Research on Revenue Insurance Premium Ratemaking of Jujube Based on Copula-Stochastic Optimization Model

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Li-Mei Qi ◽  
Ruo-Yu Yao ◽  
Xing-Zhe Zhang ◽  
Yu-Jing Zhang ◽  
Xiao-Yin Wang ◽  
...  
Keyword(s):  
Stochastic Optimization ◽  
Optimization Model ◽  
Unit Area ◽  
Copula Function ◽  
Insurance Premium ◽  
Distribution Functions ◽  
Risk Minimization ◽  
Premium Rate ◽  
Empirical Copula ◽  
Revenue Insurance

During the process of jujube planting, there are not only natural risks caused by natural disasters but also market risks caused by price factors. In the study, firstly, wavelet analysis method was used to stabilize the jujube yield per unit area and the jujube price from 1997 to 2018 in Aksu region, Xinjiang, China. Secondly, EasyFit software was used to fit the distribution functions of yield per unit area and price, respectively. Thirdly, the optimal Copula function which connects the marginal distribution functions and its joint distribution function was selected with the principle of “the minimum square distance from the empirical Copula function.” Finally, taking the premium rate and the insurance amount as two decision variables, the farmer’s risk minimization as the objective function, around the four constraints of functions and role of insurance, the nonspeculative nature of insurance, the sustainability of insurance, and the moral hazard factors and the farmers’ willing to participate in insurance, the Copula-stochastic optimization model was set up to determine the premium rate of jujube revenue insurance in Aksu region.

scholarly journals Stochastic Optimal Dispatch of Virtual Power Plant considering Correlation of Distributed Generations

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Jie Yu ◽  
Qizhi Feng ◽  
Yang Li ◽  
Jinde Cao
Keyword(s):  
Power Plant ◽  
Stochastic Optimization ◽  
Optimization Model ◽  
Mathematic Model ◽  
Distribution Functions ◽  
Virtual Power ◽  
Deterministic Optimization ◽  
Distributed Generations ◽  
Virtual Power Plant ◽  
Optimal Dispatch

Virtual power plant (VPP) is an aggregation of multiple distributed generations, energy storage, and controllable loads. Affected by natural conditions, the uncontrollable distributed generations within VPP, such as wind and photovoltaic generations, are extremely random and relative. Considering the randomness and its correlation of uncontrollable distributed generations, this paper constructs the chance constraints stochastic optimal dispatch of VPP including stochastic variables and its random correlation. The probability distributions of independent wind and photovoltaic generations are described by empirical distribution functions, and their joint probability density model is established by Frank-copula function. And then, sample average approximation (SAA) is applied to convert the chance constrained stochastic optimization model into a deterministic optimization model. Simulation cases are calculated based on the AIMMS. Simulation results of this paper mathematic model are compared with the results of deterministic optimization model without stochastic variables and stochastic optimization considering stochastic variables but not random correlation. Furthermore, this paper analyzes how SAA sampling frequency and the confidence level influence the results of stochastic optimization. The numerical example results show the effectiveness of the stochastic optimal dispatch of VPP considering the randomness and its correlations of distributed generations.

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.

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

scholarly journals Revenue Insurance for Georgia and South Carolina Peaches

2000 ◽  
Vol 32 (1) ◽  
pp. 123-132 ◽  
Author(s):  
Stephen E. Miller ◽  
Kandice H. Kahl ◽  
P. James Rathwell
Keyword(s):  
South Carolina ◽  
High Coverage ◽  
Premium Rate ◽  
Revenue Insurance ◽  
Statistical Sense ◽  
The Mean ◽  
Premium Rates ◽  
Insurance Rates ◽  
High Yields ◽  
Yield Insurance

AbstractWe estimate actuarially fair premium rates for yield and revenue insurance for Georgia and South Carolina peaches. The premium rates for both products decrease at a decreasing rate as the mean farm-level yield increases. In general, the premium rate for revenue insurance exceeds the premium rate for yield insurance for a given coverage level and expected yield. Although the revenue and yield insurance rates differ in a statistical sense, they do not appear to differ in an economic sense except at high coverage levels for growers with very high yields.

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