- Open Access
- Authors : Dr. A Sahaya Sudha
- Paper ID : IJERTV8IS120283
- Volume & Issue : Volume 08, Issue 12 (December 2019)
- Published (First Online): 30-12-2019
- ISSN (Online) : 2278-0181
- Publisher Name : IJERT
- License: This work is licensed under a Creative Commons Attribution 4.0 International License
Application of EDAS Method on Water Requirement in Agriculture
Dr. A. Sahaya Sudha Assistant Professor, Department of Mathematics Nirmala College for Women, Coimbatore, India
Abstract Muticriteria Decision making is the latest developing mathematical technique which is being followed in management practices. Due to the complexity of a given situation the expected results are ambiguous and vague in the decision making process. This can be done by using the Mathematical analysis of a given situation by using one of the MCDM Methods called Evaluation based on Distance from Average solution (EDAS) method. In this paper an agricultural situation in a locality is considered where various parameters on water management in Agricultural crops are considered. So, to find a better alternative a study has been taken on different crops of different durations, water consumption, yield, market pricing and is mathematically evaluated by applying EDAS method for efficient water management practices for an agriculturist.
Keywords MCDM, water Management, EDAS, crop selection, irrigation
-
INTRODUCTION
Multicriteria Decision making (MCDM) is a process of arriving at the best appropriate solution from a set of available alternatives in relation to a set of evaluation criteria. The MCDM methods have been discussed by various authors and has been published in a number of scientific and technical journals and proposed methods for solving various MCDM problems in areas of Economics[2,4], Management[8,9], production[10,11],sustainabledevelopment,[3,5], construction, [3,13,14] Logistics, [12]to name a few. The Evaluation Based on Distance from Average Solution (EDAS) is a new and efficient MCDM method. This was proposed and further extended EDAS method for multi
-
MATHEMATICAL ALGORITHM FOR THE PROPOSED METHOD
The Mathematical procedure for the EDAS method for a decision making problem with n criteria and m alternatives can analyzed as per the following procedures:
Step: 1 Select the available alternatives and the most important criteria which describes the alternatives to construct a Decision Making Matrix D as:
C1 C2 C3 Cn
A1 X11 X12 X13 X1n
A2 x21 x22 x23 X2n
D = A3 x31 x32 x33 X3n
. . . . . .
. . . . . .
. . . . . .
Am xm1 xm2 xm3 xmn
Where w = [w1 , w2 , w3 ,…, wn] ———— (1)
Let A1 , A2 , A3 ,…, Am are possible alternatives among which decision makers have to choose C1 , C2 , C3 ,…, Cn are criteria with which alternatives performance are measured, xij is the performance value of alternatives Ai with respect to criterion Cj , wj is the weight of criterion Cj and all xij are positive numbers
Step 2: Determine the average solution (AVj) according to all the criteria as per the formula:
n
x
i ij
criteria Decision Making by Keshavarz Ghorabaee et.al., [1,6,7]. The desirability of alternatives in this method is
AV j
1 ——————- (2)
n
determined based on distances of them from an average solution (AV). Here we have two measures of dealing with the desirability of the alternatives. The first measure is the positive distance from average (PDA), and the second is the negative distance from average (NDA). These measures shows the difference between each solution (alternative) and the average solution. The evaluation of the alternatives is made according to higher values of PDA and lower values of NDA. Higher values of PDA and/or lower values of NDA represent that the solution (alternative) is better than average
Step 3: The Positive Distance from average (PDA) is
calculated according to the criteria which are beneficial or non
beneficial:
If jth criterion is beneficial PDA max(0,( X ij AVij )))
j
j
ij AV
If jth criterion is non beneficial
solution.
PDA max(0,( AVj X ij ))
(3)
j
j
ij AV
Step 4: Calculate the Negative Distance from average (NDA) is calculated according to the criteria
we have considered the main criteria as water requirement in this paper. The Criteria C1, C2 and C3 are Income, Water
If jth criterion
is beneficial
Consumption and Water Cost .The above criteria is arrived
max(0, AV X ))
based on the availability and usage of water for a given crop
NDAij
j ij
AVj
and also the cost of water are worked out based on the yield and market price. It may also be noted that the other cost of
If jth criterion is non beneficial
inputs are not taken here since this is not significant in this
NDAij
max(0,( X ij AVij ))). (4)
AVj
study even though the other factors also influence the Economics of Farming activity.
Step 5: The Weighted sum of PDA is obtained from the Average Matrix:
m
m
SPi wj PDAi j
j 1
where wj denotes the weight of the criteria j
Step 6: The Weighted sum of NDA is obtained from the Average Matrix:
m
TABLE I CRITERIA DESCRIPTION
Criteria
Description
Income
Income obtained from crop cultivation
Water consumption
Quantity of Water required for the crop
Water Cost
Cost involved in the water usage in crop cultivation
Criteria
Description
Income
Income obtained from crop cultivation
Water consumption
Quantity of Water required for the crop
Water Cost
Cost involved in the water usage in crop cultivation
TABLE II
Criteria
Alternatives
Income(C1)
Water Consumption(C2)
Water Cost(C3)
A1
188.57
13.71
0.07
A2
4165.00
18.33
0.00
A3
1894.23
23.08
0.01
A4
489.09
15.15
0.03
A5
188.57
11.43
0.06
A6
1087.50
14.58
0.01
A7
261.67
27.50
0.11
A8
858.89
14.44
0.02
A9
850.00
33.33
0.04
Criteria
Alternatives
Income(C1)
Water Consumption(C2)
Water Cost(C3)
A1
188.57
13.71
0.07
A2
4165.00
18.33
0.00
A3
1894.23
23.08
0.01
A4
489.0
15.15
0.03
A5
188.57
11.43
0.06
A6
1087.50
14.58
0.01
A7
261.67
27.50
0.11
A8
858.89
14.44
0.02
A9
850.00
33.33
0.04
DECISION MATRIX- DRIP IRRIGATION
i
i
SNi
j 1
wj NDA j
Step 7 : The Normalized values of SPi alternatives is calculated as follows:
and SNi for all
NSPi
SPi
max (SP )
i i
SN
i
i
NSN i 1
max i (SN i )
Where NSPi and NSNi denote the normalized weighted sum of PDA and NDA respectively
Step 8: The appraisal score ASi for all alternatives is obtained as:
AS 1 (NSP NSN )
Criteria
Alternative
Income(C1)
Water Consumption(C2)
Water Cost(C3)
A1
111.43
20.00
0.18
A2
1726.67
26.67
0.02
A3
1807.69
36.54
0.02
A4
429.09
19.39
0.05
A5
111.43
17.86
0.16
A6
975.00
23.33
0.02
A7
171.67
30.00
0.17
A8
768.89
23.33
0.03
A9
775.00
50.00
0.06
Criteria
Alternative
Income(C1)
Water Consumption(C2)
Water Cost(C3)
A1
111.43
20.00
0.18
A2
1726.67
26.67
0.02
A3
1807.69
36.54
0.02
A4
429.09
19.39
0.05
A5
111.43
17.86
0.16
A6
975.00
23.33
0.02
A7
171.67
30.00
0.17
A8
768.89
23.33
0.03
A9
775.00
50.00
0.06
TABLE III
i 2 i
i
where 0 ASi 1
DECISION MATRIX – FLOOD IRRIGATION
Step 9: The alternatives are ranked according to the decreasing values of appraisal score (ASi). The alternative with the highest ASi is the best choice among the alternatives.
-
CASE ANALYSIS
In this paper a decision making approach with an example of an agricultural activity is considered. An analysis of crops of different durations and different water requirement along with the production of economies is considered in a farming activity in a particular locality. A data pertaining to nine different types of crops based on their duration along with Income, Water Cost and the Quantity of water required using both Drip and Flood Irrigation methods is calculated as per the cropping pattern. According to the farmers requirement 9
Step 1: The average solution for Drip Irrigation is calculated from the Table 2
assigned alternatives A1, A2, A3, A4, A5, A6, A7, A8, A9 are
( AV
9983.28
)(C ) 1109.28 , (AV )(C )= 19.06,
selected where the alternatives A1, A2 &, A3 are Long
j 2
j 1 9
duration crops of 300-360 days , A4, A5,& A6 are medium duration crops of 120 -140 days and A7, A8,& A9 are short duration crops from 60-90 days. Here the economics of scale are worked out by giving the best option for a farmer to decide and cultivate a crop which is best suited along with the availability of resources where the main emphasis is on water conservation. Since water is the main source for agriculture
( AVj)(C3)= 0.038
The average solution for Flood Irrigation is calculated from the Table III
(AVj)(C1) =764.10 , (AVj) (C2) = 27.46, (AVj) (C3) = 0.08
Step2: The Positive distance from average (PDA) for Drip Irrigation is
TABLE V
Alternatives
SPi
SNi
NSPi
NSNi
ASi
Ranking
A1
0.0896
0.6983
0.1287
0.0000
0.0643
8
A2
0.6910
0.0000
0.9919
1.0000
0.9959
1
A3
0.6967
0.1091
1.0000
0.8437
0.9219
2
A4
0.2389
0.1447
0.3430
0.7928
0.5679
5
A5
0.1154
0.6183
0.1656
0.1145
0.1401
7
A6
0.3711
0.0000
0.5327
1.0000
0.7664
3
A7
0.0000
0.6832
0.0000
0.0217
0.0108
9
A8
0.2554
0.0000
0.3667
1.0000
0.6833
4
A9
0.0664
0.2709
0.0953
0.6120
0.3537
6
Alternatives
SPi
SNi
NSPi
NSNi
ASi
Ranking
A1
0.0896
0.6983
0.1287
0.0000
0.0643
8
A2
0.6910
0.0000
0.9919
1.0000
0.9959
1
A3
0.6967
0.1091
1.0000
0.8437
0.9219
2
A4
0.2389
0.1447
0.3430
0.7928
0.5679
5
A5
0.1154
0.6183
0.1656
0.1145
0.1401
7
A6
0.3711
0.0000
0.5327
1.0000
0.7664
3
A7
0.0000
0.6832
0.0000
0.0217
0.0108
9
/td>
A8
0.2554
0.0000
0.3667
1.0000
0.6833
4
A9
0.0664
0.2709
0.0953
0.6120
0.3537
6
RANKING OF FLOOD IRRIGATION
PDA (C
max(0,(x11 AVj (c1))
)
max(0,0- 1109.28)
0.0000
11
PDA (C
11 Av j (C1)
max(0,( AV j (c2 ) X12 ))
)
1109.28
max(0,(19.06- 13.71)
0.2806
12 12
Av j (C2 )
19.06
Similarly other values for Positive distance from average (PDA) for Drip Irrigation is calculated
Step: 3 The Negative Distance from average (NDA) for Drip Irrigation is
NDA (C )
11 11
max(0,( AVj (c1 ) X12 ))
Av j (C2 )
max(0,(1109.28- 188.57))
1109.28
0.8300
NDA (C )
12 12
max(0,(x12 AVj (c1 ))
Av j (C1 )
max(0,(13.71- 19.06))
0
19.06
Similarly the other values also calculated
Step: 4 Weighted sum of PDA is calculated by multiplying the weights of each value in Step 2
where w1=0.33, w2=0.33, w3=0.33
Step: 5 Weighted sum of NDA (SNi)) is calculated by multiplying the weights of each value in Step 3 where w1=0.33, w2=0.33, w3=0.33
Step: 6 The following table shows the Normalized values of SPi ,SNi and the Appraisal score (ASi) is obtained using the Formula given in the Step7and step8 of Algorithm
TABLE IV
NORMALIZED VALUES OF SPI & SNI DRIP IRRIGATION
Alternatives
SPi
SNi
NSPi
NSNi
ASi
Ranking
A1
0.0926
0.5516
0.0762
0.4171
0.2467
7
A2
1.2149
0.0000
1.0000
1.0000
1.0000
8
A3
0.4617
0.0695
0.3800
0.9266
0.6533
1
A4
0.1389
0.1845
0.1143
0.8050
0.4597
4
A5
0.1322
0.4503
0.1088
0.5242
0.3165
6
A6
0.2955
0.0065
0.2432
0.9932
0.6182
2
A7
0.0000
0.9464
0.0000
0.0000
0.0000
9
A8
0.2694
0.0745
0.2218
0.9213
0.5715
3
A9
0.0023
0.3242
0.0019
0.6575
0.3297
5
Similarly we can calculate the values for Flood Irrigation also and the values are obtained in Table 5
Fig 1: Pictorial Representation of Ranking Drip & Flood Irrigation
-
CONCLUSIONS
In this paper the EDAS method is applied to solve a multi criteria decision making problem of finding the best crop suited on the basis of minimum water requirement along with a higher income for a farmer. Here the best alternative of crop is suggested by considering lower cost and less usage of water with a higher income. The ranking of the alternatives for Drip Irrigation method in order are A3 > A6 > A8 > A4 > A9 > A5 > A1 > A2 > A7. Results indicate that A3 is the best alternative with ASi value of 0.6533.The ranking of the alternatives for Flood Irrigation in order are A2 > A3 > A6 > A8 > A4 > A9 > A5
> A1 > A7. Results indicate that A2 is the best alternative with ASi value of 0.9959 wherein A2 which is the best alternative in Flood Irrigation method. This method can be used to arrive at a decision for any number of crops also with number alternatives. Similarly this ranking also can be used for different durations based crops as per the above results, where Crop A3 is suited in long duration, A6 is suited in terms of medium duration and A8 is suited for short duration in the case of Drip Irrigation .In case of Flood Irrigation the best crop is A2, A6 and A8 for long duration, Medium duration and short duration crops respectively.
REFERENCES
-
Amiri M, Keshavarz Ghorabaee M, Turskis Z, Zavadskas E.K 2016., Extended EDAS method for fuzzy multi-criteria decision-making an application to supplier selection. International Journal of Computers Communications &Control, 11(3): 358-371.
-
Amiri M, Keshavarz Ghorabaee M, Turskis Z, Zavadskas E.K 2017., Multi-criteria group decision-making using an extended EDAS method with interval type-2 Fuzzy sets, E&M Ekonomie a Management,20(1): 4868.
-
Cevik Onar S , Kahraman C, Keshavarz Ghorabaee M, Oztaysi B, Yazdani M,Zavadskas E.K.,2017 Intuitionistic fuzzy EDAS method: An application to olidwaste disposal site selection, Journal of Environmental Engineering and Landscape Management 25(1): 11.
-
Ghadikolaei,A.S.,Esbouei,S.K.,Antucheviciene ,J 2014 Applying fuzzy MCDM for financial performance evaluation of Iranian companies. Technological and Economic Development of Economy,20(2) :274-291
-
Ghosh,S ,Chakraborthy,T …Saha, S. Majumder,M., Pal,M 2016,.Development of the local suitability index for wave energy production by ANN and MCDM techniques .Renewable and Sustainable Energy Reviews 59:1017-1028.
-
Keshavarz Ghorabaee M, Olfat L, Turskis Z, Zavadskas E.K., 2015,Multicriteria inventory classification using a new method of evaluation based on distance from average solution (EDAS). Informatica, 26(3): 435-451.
-
Keshavarz Ghorabaee M, Stanujkic D, Turskis Z, Zavadskas E.K.,2017, An extension of the EDAS method based on the use of interval grey numbers, Studies in Informatics and Control 26(1):51.
-
Li, M., Jin, L., &Wang, J 2014,A new MCDM method combining QFD with TOPSIS for knowledge management system selection from the user`s perspective in intuitionistic fuzzy environment .Applied soft computing, 21: 28-37.
-
Mardani,A.,Juosh,A.,Zavadskas,E.K.,Zakuan,N.,Valipour,A.,&Kazemi lari,M 2014, Proposing new hierarchical framework for the evaluation of quality management practices: a new combined fuzzy hybrid MCDM approach. Journal of Business Economics and Management,17(1):1-16.
-
Pavlovskis, M., Antucheviciene, J., &Migilinskas, D. 2014,Application of MCDM and BIM for Evaluation of Asset Redevelopment Solutions. Studies in Informatics and Control, 25(3) : 293-302.
-
Ren,J., Manzardo,A.,Mazzi,A.,Zuliani,F.,&Scipioni,2015, A.Prioritization of bioethanol production pathways in China based on life cycle sustainability assessment and multicriteria decision making. The International Journal of Life cycle Assessment ,20(6) :.842-853.
-
Stevic Z, Vasiljevic M and Veskovic S,2016, Evaluation in logistics using combined AHP and EDAS method, in: XLIII International Symposium on Operational Research, Serbia, : 309311.
-
Zavadskas, E.K., Turksis, Z., and Antucheviciene, J . 2015, Selecting contractor by using a Novel Method for Multiple Attribute Analysis: Weighted Aggregated Sum Product Assessment with Grey values (WASPAS-G).Studies in Informatics and Control, 24(2):141-150.
-
Zavadskas, E.K., Turksis, Z., Volvaciovas, R., Kidiene, S.2013 Multicriteria assesment model of technologies. Studies in Informatics and Control, 22(4):.249-258.