An Integrated Fuzzy Multi Criteria Group Decision Making Model for Handling Equipment Selection

Abstract

The problem of handling equipment selection plays a significant role in the total cost of a mining project; so that it can affect the activity and continuity of the project and is a strategic problem. In this study, an integrated model based on two fuzzy multi-criteria decision making techniques for handling equipment selection is proposed. The proposed evaluation model is derived from group decision making, fuzzy set theory, analytical hierarchy process (AHP), and Technique to Order Preference by Similarity to Ideal Solution (TOPSIS) methods. The fuzzy AHP (FAHP) method is utilized to calculate the relative importance of the evaluation criteria, then, fuzzy TOPSIS (FTOPSIS) is applied for evaluating the feasible handling equipment in order to select the best handling system among a pool of the possible alternatives. The model is applied for a real world case study to demonstrate the capability and effectiveness of the proposed model. To investigate the result sensitiveness to the changes of the criteria weights, a sensitivity analysis is finally conducted.

A software prototype for material handling equipment selection for construction sites

“…The developed methodology could calculate the crane rotation point and assist in modifying the boom configuration rather than relocating the unit. Yazdani-Chamzini [24] employed two fuzzy MCDM methods, i.e. FAHP and FTOPSIS to select the most suitable MHE under an uncertain environment.…”

Urban stormwater construction method selection using a hybrid multi-criteria approach

“…Most of the existing fuzzy AHP models employ triangular typed fuzzy numbers (e.g. [36,71]). Buckley [10] developed a fuzzy AHP model using trapezoidal fuzzy numbers.…”

Combination of Fuzzy-Ahp and Dematel-Anp With Gis in a New Hybrid McDm Model Used for the Selection of the Best Space for Leisure in a Blighted Urban Site

“…Another question is how much importance of a criteria has compared with another criteria with respect to the interests or preferences of experts (Karsak et al 2003). The relative importance can be determined using a scale of 1 to 9, representing a range from equal, moderately, strongly, very strongly (1, 3, 5 and 7 respectively), to extreme importance (9) and importance of 2, 4, 6, and 8 as the intermediate importance for the preference scale (Chen et al 2010;Liou 2012;Saaty 1980Saaty , 1996Shen et al 2011;Yazdani-Chamzini 2014;Gudienė et al 2014;Kaya, Kahraman 2014). Finally, after the computation of the relationship of the super-matrix and the comprehensive evaluations, it is possible to derive the interdependence of each valuation criteria and options and the weighting of priorities.…”