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1.
A statistical model for shutdowns due to air quality control for a copper production decision support system
Khalid Aboura, 2015, original scientific article

Abstract: Background: In the mid-1990s, a decision support system for copper production was developed for one of the largest mining companies in Australia. The research was conducted by scientists from the largest Australian research center and involved the use of simulation to analyze options to increase production of a copper production facility. Objectives: We describe a statistical model for shutdowns due to air quality control and some of the data analysis conducted during the simulation project. We point to the fact that the simulation was a sophisticated exercise that consisted of many modules and the statistical model for shutdowns was essential for valid simulation runs. Method: The statistical model made use of a full year of data on daily downtimes and used a combination of techniques to generate replications of the data. Results: The study was conducted with a high level of cooperation between the scientists and the mining company. This contributed to the development of accurate estimates for input into a support system with an EXCEL based interface. Conclusion: The environmental conditions affected greatly the operations of the production facility. A good statistical model was essential for the successful simulation and the high budget expansion decision that ensued.
Keywords: decision support system, simulation, statistical modelling
Published: 28.11.2017; Views: 440; Downloads: 258
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2.
Decision making under conditions of uncertainty in agriculture
Karmen Pažek, Črtomir Rozman, 2009, review article

Abstract: In decision under uncertainty individual decision makers (farmers) have to choose one of a set number of alternatives with complete information about their outcomes but in the absence of any information or data about the probabilities of the various state of nature. This paper examines a decision making under uncertainty in agriculture. The classical approaches of Wald’s, Hurwicz’s, Maximax, Savage’s and Laplace’s are discussed and compared in case study of oil pumpkin production and selling of pumpkin oil. The computational complexity and usefulness of the criterion are further presented. The article is concluded with aggregate the results of all observed criteria and business alternatives in the conditions of uncertainty, where the business alternative 1 is suggested.
Keywords: uncertainty, Wald’s, Hurwicz’s, Maximax, Savage’s and Laplace’s criterion, decision support system, agriculture, oil crops
Published: 20.07.2017; Views: 500; Downloads: 75
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3.
Application of analytical hierarchy process in agriculture
Karmen Pažek, Črtomir Rozman, 2005, original scientific article

Abstract: Hierarchical decision models are a general decision support methodology aimed at the classification or evaluation of options that accur in desion-making processes. Decision models are typically developed through the decomposition of complex decision problems into smaller and less comple subproblems. This paper presents an approach to the development and implementation of multicriteria decision model based on Analytical Hierarchy Process - AHP (Expert Choice, EC). Likewise, the AHP is used as a potential multicriteria decision making method for application in agriculture. In order to show the implementation of explained MCDA methods in real situation in agriculture, theapplication of AHP on a sample model farm is presented in the second part of the article.
Keywords: multicriteria decision analysis, MCDA, analytical hierarchy process, AHP, decision support system, DSS, agriculture
Published: 20.07.2017; Views: 680; Downloads: 150
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