An Application Of The Topsis Method To Solve Hydraulic Excavator Selection Problem In Mining

Society for Mining, Metallurgy & Exploration
M. Yavuz
Organization:
Society for Mining, Metallurgy & Exploration
Pages:
3
File Size:
134 KB
Publication Date:
Jan 1, 2008

Abstract

Decision Making (DM) can be defined as a selection process of the best one among the alternatives sets in order to obtain goal, and mostly has an uncertain situation [7]. Every mining engineer is subjected to a number of mining DM problems in daily mining operations. In reality, all stages of mining have its own DM problems. Most of time, engineers do not use scientific methods for DM problems. These problems can mostly be solved by the engineers according to their past experiences and practical studies. Mining engineers often use their intuition in DM process. Experience and intuition have been central to DM because of the frequent lack of quantitative data including geology, grade distribution and ground condition, as well as environmental, social and economic factors [8]. In decision process, linguistic variables become in question and decision makers may not know how these variables are computed [9]. So, the DM process may be qualitative, quantitative or combination of the two. The problem structuring and analysis process is conceptualized in Figure 1 [8]. The qualitative analysis is based primarily on the judgment, knowledge and experience of an expert (or team of experts). In a quantitative analysis, the focus is on facts and the data associated with a problem and a mathematical formulation that encompasses the objectives, variables and constraints of the particular problem. The quantitative analysis has traditionally been the subject of operation research and management science [8].
Citation

APA: M. Yavuz  (2008)  An Application Of The Topsis Method To Solve Hydraulic Excavator Selection Problem In Mining

MLA: M. Yavuz An Application Of The Topsis Method To Solve Hydraulic Excavator Selection Problem In Mining. Society for Mining, Metallurgy & Exploration, 2008.

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