Supply chain coordination based on a buyback contract under fuzzy random variable demand

2014 ◽  
Vol 255 ◽  
pp. 1-16 ◽  
Author(s):  
Biao Zhang ◽  
Songfeng Lu ◽  
Di Zhang ◽  
Kunmei Wen
Keyword(s):  
Supply Chain ◽  
Supply Chain Coordination ◽  
Fuzzy Random Variable ◽  
Random Variable ◽  
Variable Demand ◽  
Buyback Contract ◽  
Fuzzy Random

Risk measurement and optimization model of coal generation contracts for the difference between prospect M-V and normal triangular fuzzy stochastic variables

Kybernetes ◽  
2016 ◽  
Vol 45 (8) ◽  
pp. 1323-1339 ◽  
Author(s):  
Weiwei Li ◽  
Chong Wu ◽  
He Dong ◽  
Huan Wang ◽  
Mei Li
Keyword(s):  
Supply Chain ◽  
Fuzzy Random Variable ◽  
Random Variable ◽  
Decision Makers ◽  
Spot Price ◽  
Supply Chain System ◽  
Content Type ◽  
Measurement Models ◽  
Risk And Benefit ◽  
Fuzzy Random

Purpose Coal and power generation are related upstream and downstream industries. Coal price marketization and electricity price regulation have caused the price of coal to be sensitive to the benefits of generators. The paper aims to discuss these issues. Design/methodology/approach As a financial tool, contracts for differences can both help balance interests and reduce risks caused by spot price fluctuation. This thesis regards coal demand as a triangular fuzzy stochastic variable while directing a levelling consideration towards risk returns for coal and power enterprises that are involved in coal generation contracts for differences. Risk and benefit measurement models were established between coal suppliers and power generators, and risk and benefit balance optimization models for contract negotiation were constructed. Findings A numerical example showed that the above models can be effectively used to avoid the risks of coal-electricity parties. Originality/value This thesis regards coal demand as a triangular fuzzy random variable while directing a levelling consideration towards the risk return to coal and power enterprises that are involved with coal generation contracts for differences. The features of this thesis are the following: demand information is regarded as a fuzzy random variable instead of a random variable. With historical data, sales experience and increasingly clear macro-economic conditions, coal and power enterprises are able to make a fuzzy decision – to a certain extent – when the transaction approaches. Accurate market information enables the supply chain system to satisfy the clients’ needs better, improve the profit level or avoid severe financial damages; by developing a feasible set of contracts for different parameters, it is possible to estimate whether the price difference enables supply chain coordination, requires changes or gives accounts to all involved parties of the supply chain; and without the assumption that the traditional M-V rule is unfavourable to decision makers, this thesis proposes the prospect M-V rule, which involves decision makers’ projections of future coal generation prices and enables wide applicability of the response method to contracts for differences.

scholarly journals Do the buyback contracts of undistributed stocks coordinate the supply chain?

2020 ◽  
Vol 19 (4) ◽  
pp. 461-492
Author(s):  
Irina V. Berezinets ◽  
◽  
Nikolay A. Zenkevich ◽  
Alina S. Rucheva ◽  
Natalia K. Nikolchenko ◽  
...  
Keyword(s):  
Supply Chain ◽  
Supply Chain Coordination ◽  
Market Price ◽  
Random Variable ◽  
Nash Solution ◽  
Product Demand ◽  
General Terms ◽  
Buyback Contract ◽  
Practical Feasibility ◽  
Independent Chain

The concept of supply chain coordination implies that it is possible to obtain an optimal result for both independent chain participants and supply chain due to participants’ coordinated actions. This paper examines the question whether a buyback contract will be coordinating or not. The authors argue that a coordinating buyback contract should have the following substantive properties: practical feasibility, collective and individual rationality. The paper off ers a mathematical defi nition of a coordinating buyback contract which highlights these properties. Entering into buyback contract process is considered as a two-step game of two players (a supplier and retailer) on the assumption that the players are risk neutral and make decisions with full information available, the market price is fixed, and the product demand is a random variable. The authors demonstrate that the buyback contract does not coordinate the chain, however, there has been obtained a non-empty set of eff ective contracts depending on the buyback price. For such contracts, the defi nition of “conditional coordination” is given to introduce the property of a supplier’s partial rationality; its existence was proved. The findings reveal that the choice of buyback price affects the allocation of profits between chain participants so the decision on its choice must be cooperative. To substantiate the nature of cooperative choice of conditionally coordinating contracts, the asymmetric Nash solution is considered. All results were obtained both in general terms and under the assumption that the product demand has uniform distribution. For the latter case, the conditionally coordinating contract parameters were found and it was justified that the conclusion of such a contract is possible only when a supplier has greater bargain power than a retailer.

scholarly journals On Distribution Characteristics of a Fuzzy Random Variable

2018 ◽  
Vol 47 (2) ◽  
pp. 53-67 ◽  
Author(s):  
Jalal Chachi
Keyword(s):  
Probability Theory ◽  
Distribution Function ◽  
Cumulative Distribution Function ◽  
Random Variables ◽  
Fuzzy Random Variable ◽  
Random Variable ◽  
Cumulative Distribution ◽  
Distribution Characteristics ◽  
Fuzzy Random Variables ◽  
Fuzzy Random

In this paper, rst a new notion of fuzzy random variables is introduced. Then, usingclassical techniques in Probability Theory, some aspects and results associated to a randomvariable (including expectation, variance, covariance, correlation coecient, etc.) will beextended to this new environment. Furthermore, within this framework, we can use thetools of general Probability Theory to dene fuzzy cumulative distribution function of afuzzy random variable.

The Compatibility Assessment between Voltage Sags and Equipment Tolerance Based on Fuzzy-Random Method

2012 ◽  
Vol 588-589 ◽  
pp. 458-462
Author(s):  
Zhi Jian Yuan ◽  
Yan Li
Keyword(s):  
Engineering Application ◽  
Fuzzy Random Variable ◽  
Random Variable ◽  
Assessment Model ◽  
Voltage Sags ◽  
Equipment Failure ◽  
Failure Event ◽  
Cut Set ◽  
The Impact ◽  
Fuzzy Random

The impact of voltage sags on equipment is usually described by equipment failure probability.It is generally difficult to assess and predict the probability because of the uncertainty of both the nature of voltage sags and the VTL (VTL) of equipment. By defining the equipment failure event caused by voltage sags as a fuzzy-random event, a fuzzy-random assessment model incorporating those uncertainty is developed. The model is able to convert the probability problem of a fuzzy-random variable to that of a common random variable by using λ-cut set. It is thus valuable in theoretical analysis and engineering application. The validity of the developed model is verified by Monte Carlo stochastic simulation using personal computers (PCs)as test equipment.

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