scholarly journals A FUZZY LOGIC ENHANCED BARGAINING MODEL FOR BUSINESS PRICING DECISION SUPPORT IN JOINT VENTURE PROJECTS / FUZZY LOGINIO PASIKEITIMŲ VERTINIMO METODO TAIKYMAS JUNGTINĖS VEIKLOS PROJEKTŲ VERTEI NUSTATYTI

2011 ◽  
Vol 12 (2) ◽  
pp. 234-247 ◽  
Author(s):  
Min-Ren Yan
Keyword(s):  
Decision Support ◽  
Set Theory ◽  
Joint Venture ◽  
Bargaining Model ◽  
Decision Support Model ◽  
Short Term ◽  
Bargaining Process ◽  
Pricing Decisions ◽  
Pricing Decision ◽  
Bargaining Positions

Project businesses are increasingly emerging and many companies cooperatively participate in various projects by the manner of joint venture (JV) for creating synergistic competitiveness. In a project-based short-term JV, the project tasks of JV parties can be properly allocated based on complementary specialties but the rewards sharing is always a challenge in the bargaining process. For improving the manager's reasoning process of pricing decisions, this paper incorporates game theory and fuzzy set theory for the development of a bargaining model, which can be used to estimate acceptable prices for JV parties in accordance with each party's costs and each party's need for the project's revenue. The proposed decision support model can assist JV companies to understand their bargaining positions and select a bargaining strategy in a systematic and rational manner. Irrational offers and alternatives can also be detected and eliminated during the dynamic bargaining process, so as to maintain right businesses. Santrauka Verslo projektai savo dydžiu, tematika, pobūdžiu ir kitais aspektais nuolat kinta, todėl dauguma kompanijų, siekdamos išlaikyti konkurencinį pranašumą bei rengdamos įvairius projektus, jungiasi į tam tikras jungtines įmones, kurios vykdo jungtines veiklas, skirtas tik tam projektui įgyvendinti. Tokios įmonės, kurios apribotos projekto trukmės, įgauna tam tikrų savybių, kai tikėtina nauda iš šio susijungimo yra neapibrėžta ir nuolat kinta. Šio straipsnio autoriai, siekdami pagerinti motyvacinę vadovų sistemą, priimdami sprendimus dalyvauti jungtinėje veikloje ir įvertindami priimtiną santykį tarp investuojamos sumos dydžio ir tikėtinos naudos, taiko žaidimų teoriją bei Fuzzy metodą.

scholarly journals Stockpol: A decision support model for livestock farms

1991 ◽  
pp. 137-140 ◽  
Author(s):  
P.R. Marshall ◽  
D.G. Mccall ◽  
K.L. Johns
Keyword(s):  
Land Use ◽  
Decision Support ◽  
Policy Changes ◽  
Land Area ◽  
Decision Support Model ◽  
Short Term ◽  
Financial Reports ◽  
And Performance ◽  
Individual Farm

A computer program called Stockpol is described. It is a biological model designed for decision support applications on pastoral farms. Individual farm scenarios are defined in terms of component subfiles which define stock (numbers and performance), land (area, pasture growth rates and land use), prices and constants. Physical and financial reports are available for individual scenarios, and for comparisons among scenarios. Once defined, scenarios are tested for biological feasibility by calculating if there is enough pasture cover on the farm at all times to meet animal requirements for targetperformance levels. Policies for biologically unfeasible farms can be automatically modified if necessary. Stockpol can be used to analyse long-term policy changes or short-term feed budgets, but it is not suitabIe for paddock-level feed budgeting. Keywords sheep, beef, pasture growth, pasture cover, feed budget, biological feasibility, prices, profits, computer model

Assessing desalination as a sustainable alternative using a multiple criteria decision support model

2008 ◽  
Vol 3 (3) ◽  
Author(s):  
M. B. Fernandes ◽  
M. C. Almeida ◽  
A. G. Henriques
Keyword(s):  
Decision Support ◽  
Energy Production ◽  
Fossil Fuels ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
High Energy ◽  
Economic Benefits ◽  
Multiple Criteria ◽  
Water Production ◽  
Decision Support Model

Desalination technologies provide an alternative for potable water production, having significant potential for application where fresh water scarcity exists. Potential benefits have to be balanced with other factors, such as high costs, high energy consumption, and significant environmental impacts, for the understanding of real risks and gains of desalination within the context of integrated water resources management. Multiple factors can be considered when analysing the viability of a desalination project but often a limited approach is used. The complexity in the analysis lies in finding the alternatives that obey to multiple objectives (e.g. reduced environmental impact, social acceptance, less cost associated). In this paper, development of a methodology based on multiple criteria decision support system for the evaluation and ranking the potential of desalination technologies is described and applied to a Portuguese case study. Relevant factors to the selection of desalination technologies were identified using SWOT analysis and the MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) approach was applied. Technical alternatives considered include reverse osmosis and multi-effect desalination (MED), together with energy production by fossil fuels or solar energy. Production of water by conventional approaches was also considered. Results, for non-economic benefits, show higher score for MED solar but, in the cost-benefit analysis, conventional methods of water production have higher ranking since costs of renewable energies are not yet competitive. However, even if not preferred in economic terms, desalination is ranked significantly above the conventional approaches for non-economic criteria.

scholarly journals Application of Rough and Fuzzy Set Theory for Prediction of Stochastic Wind Speed Data Using Long Short-Term Memory

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 924
Author(s):  
Moslem Imani ◽  
Hoda Fakour ◽  
Wen-Hau Lan ◽  
Huan-Chin Kao ◽  
Chi Ming Lee ◽  
...  
Keyword(s):  
Deep Learning ◽  
Wind Speed ◽  
Set Theory ◽  
Rough Set ◽  
Fuzzy Set Theory ◽  
Short Term Memory ◽  
Learning Model ◽  
Short Term ◽  
Long Short Term Memory ◽  
Deep Learning Model

Despite the great significance of precisely forecasting the wind speed for development of the new and clean energy technology and stable grid operators, the stochasticity of wind speed makes the prediction a complex and challenging task. For improving the security and economic performance of power grids, accurate short-term wind power forecasting is crucial. In this paper, a deep learning model (Long Short-term Memory (LSTM)) has been proposed for wind speed prediction. Knowing that wind speed time series is nonlinear stochastic, the mutual information (MI) approach was used to find the best subset from the data by maximizing the joint MI between subset and target output. To enhance the accuracy and reduce input characteristics and data uncertainties, rough set and interval type-2 fuzzy set theory are combined in the proposed deep learning model. Wind speed data from an international airport station in the southern coast of Iran Bandar-Abbas City was used as the original input dataset for the optimized deep learning model. Based on the statistical results, the rough set LSTM (RST-LSTM) model showed better prediction accuracy than fuzzy and original LSTM, as well as traditional neural networks, with the lowest error for training and testing datasets in different time horizons. The suggested model can support the optimization of the control approach and the smooth procedure of power system. The results confirm the superior capabilities of deep learning techniques for wind speed forecasting, which could also inspire new applications in meteorology assessment.

scholarly journals The Knowledge Exchange–Decision Support Model: application to cancer navigation programs

2013 ◽  
Vol 22 (2) ◽  
pp. 367-374 ◽  
Author(s):  
A. Fuchsia Howard ◽  
Kirsten Smillie ◽  
Vivian Chan ◽  
Sandra Cook ◽  
Arminee Kazanjian
Keyword(s):  
Decision Support ◽  
Knowledge Exchange ◽  
Decision Support Model ◽  
Model Application ◽  
Support Model
Sign in / Sign up

Export Citation Format

Share Document