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Multi criteria decision techniques were developed profusely in the 1960s. Classic methods come from that decade, when Goal Programming and ELECTRE method were proposed. On the 1970s new methods and refinements of existing ones were developed, and finally on the 1980s support from computer sciences has allowed a fast growth in applications and results from multiple criteria decision making techniques [30].
 \\When comparing different outranking methods, PROMETHEE stands out due to its fairly simple design, ease of computation and application and stability of results. Generalized preference functions allow hesitations in DMs' preferences and uncertainties in criteria performance values to be modeled [23]. Also, PROMETHEE to be easily adapted for group decision aid, for example by including different weighting schemes [7]. Thus, in this study, PROMETHEE is preferred to other outranking approaches, because it is perceived to be more transparent and easier to understand even for DMs not familiar with MADM. The following briefly describes the general PROMETHEE framework.\\
 \begin{table}

\begin{tabularx}{\textwidth}{XXXXXXXX}
\multirow{2}{*}{\rotatebox{90}{alternatives}}&Capital cost of EPC&Annual operation and maintenance cost&Efficiency&Capacity factor&Lifetime&Internal consumption&Resource potential\\ \cline{2-8}
&$C_1$&$C_2$&$C_3$&$C_4$&$C_5$&$C_6$&$C_7$\\ \whline
$a_1$&(1100,1450)&(11,14.5)&(25,35)&(25,40)&(20,20)&(1,1)&15000\\
$a_2$&(3000,6000)&(30,60)&(11.4,11.4)&(15,25)&(20,25)&(5,5)&500000\\
$a_3$&(6000,8000)&(250,300)&(10.3,10.3)&(15,95)&(25,25)&(15,15)&500000\\
$a_4$&(6000,6000)&(37,46)&(13,17)&(46,46)&(30,30)&(15,15)&60000\\
$a_5$&(5000,6000)&(16,25)&(12,17)&(20,44)&(30,30)&(15,15)&60000\\
$a_6$&(8000,8000)&(184,200)&(22,30)&(50,50)&(30,30)&(15,15)&60000\\
$a_7$&(3000,3000)&(250,300)&(40,40)&(85,85)&(25,35)&(8,10)&300\\
$a_8$&(1500,2000)&(75,100)&(35,40)&(90,90)&(15,30)&(2,2)&500\\
$a_9$&(3500,6000)&(350,600)&(20,23)&(87,87)&(20,30)&(10,15)&500\\
$a_1_0$&(3000,3500)&(210,245)&(35,40)&(90,90)&(20,30)&(7,10)&75\\
$a_1_1$&(1500,1500)&(75,100)&(35,40)&(90,90)&(20,30)&(5,5)&50\\
$a_1_2$&(2000,2500)&(132,165)&(35,40)&(90,90)&(20,30)&(4,4)&200\\
$a_1_3$&(2000,2500)&(160,200)&(35,35)&(85,85)&(20,30)&(5,10)&1275\\
$a_1_4$&(1400,3200)&(0,1)&(85,85)&(90,90)&(0.5,4.5)&(0,0)&10\\
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\caption{Measures of each criterion for all the alternatives}
\end{table}
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