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This paper considers a dynamic pricing problem for selling a given stock of a perishable product over a finite time horizon. We model the uncertain demand as random fuzzy variable and study the pricing problem in a random fuzzy environment. The retailer's dynamic pricing problem is formulated as three types of random fuzzy programming models-expected revenue maximization model, (α, β)-revenue...
This paper formulates a schema matching model to analyze the model selection problem arising from pattern recognize and schema matching between infrastructures and different type build-operate-transfer (BOT) project. Through systematical review, an analysis of relevant literature and cases analysis yielded significant factors that would have a certain impact on the feasibility of any BOT project....
The abundant market participants and transactions, as well as the flexibility of the power system planning and operation make tremendous challenges to the transmission investment. According to the real-option characteristics of transmission investment, the framework of the transmission investment decision is given. Then the market-clearing midel is bulit to realize the most efficient operation of...
This paper considers a new equilibrium pricing vector with various types of investor's subjectivity based on the standard Mean-Variance theory. In order to present each investor's subjectivity, the fuzzy theory is introduced. In a way similar to the traditional MV-based equilibrium approach, the analytical equilibrium pricing vector is obtained using the degree of credibility considering credibility...
Any single one of the Auto-Regressive (AR) model, Moving Average (MA) model and Auto-Regressive and Moving Average (ARMA) model can not match the complex time-series data of electricity price, consequently the traditional Box-Jenkins method can not solve the forecasting of electricity price well. In this paper, fuzzy Box-Jenkins approach for modeling and short-term forecasting of the electricity price...
In a two-stage supply chain composed of one supplier and one retailer, the supply chain models in a fuzzy demand environment is researched. A positive triangular fuzzy number is used to model the external market demand. Using the method of fuzzy cut sets theory, the models of centralized decision-making and returns policy are built, and their optimal policies are also proposed. It shows that the optimal...
A two-level supply chain in fuzzy environment with one supplier and two competing manufacturers is considered in this paper. The fuzzies are with the demand parameters, how the firms to make their own decisions considering the competitive factor and fuzzy demand are explored under the centralized channel case and decentralized channel case. At last, a numerical studies is given.
Though the price of M&A has already been studied based on classical NPV model, which is not adaptable for real uncertain situation. This paper presents a new approach of measuring the target enterprise value of M&A, consisting of two parts, one is measured by NPV model and another is measured by real options model, which can be integrated to calculate the target enterprise by introducing synergy...
Knowledge of customer reservation price aids manager in implementing many marketing strategies such as dynamic pricing, bundling sales, and target promotion etc. This paper investigated how cognition factors affected different customer segment's reservation price distribution. Utility of information products usually can not be quantitatively measured like that of physical products, and contrarily,...
Taking the Knightian uncertainty of financial market into consideration, the randomness and fuzziness of stock price should been evaluated by both probabilistic expectation and fuzzy expectation. We make use of parabolic type fuzzy numbers to discuss the fuzzy binomial option pricing model with uncertainty of both randomness and fuzziness, and derive expression for the fuzzy risk neutral probabilities,...
In addition to considering construction costs, real estate project pricing still needs to consider market condition, socio-economic, natural and physical, road traffic and building situations, the income level of residents as well as the influence of national policy and many other factors, due to extreme complexity, unclarity, difficulty in determinacy and quantization of these factors, in real estate...
Learning from the experience of transmission-distribution (T&D) regulation in developed countries and actual situation in China, an incentive pricing regulation model based on the optimal fuzzy algorithm and data envelopment analysis (DEA) for T&D utilities is presented in this paper. First, FC2R model based on C2R method of DEA is established in which L-R fuzzy number and is integrated. Second,...
Employment competition is becoming increasingly fierce nowadays, so it is essential that the individual human capital relative value of college graduates be evaluated which provides some reference for the divergent selection between graduates and enterprises. This paper designs the corresponding evaluation index system on the basis of theoretical analysis, and then the fuzzy comprehensive is applied...
The importance of efficient and effective charging methodologies to regulatory authorities has resulted in a significant amount of research into methods for deriving economic charges. The majority of the previous work is however limited on the assumption that a given future scenario or a fixed load growth rate, and the fundamental problem of uncertain future load growth rates in charging methodologies...
Marginal prices have been recognized as the core approach to the economic evaluation of generation and transmission services in an electricity market environment. In this context, this paper presents the new fuzzy optimal power flow algorithm as a model to addresses the impact of load and generation cost uncertainties in nodal marginal prices. Since loads and generation costs are represented by fuzzy...
Owing to the fluctuations in the financial markets from time to time, some input variables such as the interest rate, spot exchange rate and volatility in the Garman-Kohlhagen model can not be expected in a precise sense. Therefore, it is nature to start from the fuzzy environments of currency options markets. In this paper, we introduce fuzzy techniques and obtain the fuzzy versions of the Garman-Kohlhagen...
Some financial variables can always be observed with perturbations and be expected in the imprecise sense because of the fluctuation of financial markets. Therefore, this paper introduces fuzzy techniques, and gives a fuzzy currency options bounds pricing model. By denoting four input variables in the Garman-Kohlhagen model as triangular fuzzy numbers, the currency option price will turn into a fuzzy...
Riskless interest rate and volatility are two important variables in option pricing model, but are hard to be estimated precisely. The concept of fuzziness is used to describe these variables in this paper. We apply fuzzy set theory to the American put option valuation and extend the fuzzy option pricing model by introducing riskless interest rate and volatility as two trapezoidal fuzzy numbers. The...
In this study, a generalized Intelligent-agent-based fuzzy group forecasting model is proposed for oil price prediction. In the proposed model, some single Intelligent-agent-based predictors with much disagreement are first created for crude oil price prediction. Then these single prediction results produced by these single intelligent predictors are fuzzified into some fuzzy prediction representations...
According to the characteristic of ldquoquantity price separationrdquo under the pricing pattern of Bill of Quantities, this article utilizes the fuzzy synthesis judgment method, analyzes the price adjustment coefficient of unbalanced bid liner programming model which is established basing on the time value of capital. And then it gives the fuzzy mathematics model of the price adjustment coefficient...
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