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An integrated Principal Component Analysis and multi-objective mathematical programming approach to agile supply chain network design under uncertainty
1. | School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran |
2. | Faculty of Engineering, Urmia University, Urmia, West Azerbaijan Province, Iran |
The design of agile supply chain networks has attracted more attention in recent years according to the competitive business environment. Further, due to high degree of uncertainty in agile supply chains (SCs), developing robust and efficient decision making tools are of interest. In this study, an integrated approach based on principal component analysis (PCA) and multi-objective possibilistic mixed integer programming (MOPMIP) approaches is proposed to optimally design agile supply chain network under uncertainty. The PCA method is used for ranking and filtering the suppliers, constituting the first layer of the supply chain, based on agility criteria. The proposed MOPMIP model is employed to construct the agile supply chain network under uncertainty. In the proposed MOPMIP model, three objective functions including 1) total costs minimization, 2) total delivery time minimization and 3) maximization of flexibility are considered. An interactive fuzzy solution approach is used to solve the proposed MOPMILP model. Two numerical examples, is conducted to evaluate the performance and efficiency of the proposed integrated approach for agile supply chain network design under uncertainty.
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show all references
References:
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|
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Journal of the American Statistical Association, 2017. |
[5] |
R. Babazadeh, J. Razmi and R. Ghodsi, Supply chain network design problem for a new market opportunity in an agile manufacturing system Journal of Industrial Engineering International, 8 (2012), 19pp.
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[6] |
R. Babazadeh and J. Razmi,
A robust stochastic programming approach for agile and responsive logistics under operational and disruption risks, International Journal of Logistics Systems and Management, 13 (2012), 458-482.
doi: 10.1504/IJLSM.2012.050158. |
[7] |
M. Bachlaus, M. K. Pandey, C. Mahajan, R. Shankar and M. K. Tiwari, Designing an integrated multi-echelon agile supply chain network: A hybrid taguchi-particle swarm optimization approach Journal of Intelligent Manufacturing, 9 (2008), p747.
doi: 10.1007/s10845-008-0125-1. |
[8] |
B. W. Bolch and C. Huang,
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[9] |
M. J. Braunscheidel and N. C. Suresh,
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[10] |
T. A. Brown,
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[11] |
H. Carvalho, S. G. Azevedo and V. Cruz-Machado,
Agile and resilient approaches to supply chain management: Influence on performance and competitiveness, Logistics Research, 4 (2012), 49-62.
doi: 10.1007/s12159-012-0064-2. |
[12] |
J. Chai, J. N. Liu and E. W. Ngai,
Application of decision-making techniques in supplier selection: A systematic review of literature, Expert Systems with Applications, 40 (2013), 3872-3885.
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[13] |
A. T. Chan, E. W. Ngai and K. K. Moon,
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[14] |
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|
[15] |
M. Christopher,
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doi: 10.1016/S0019-8501(99)00110-8. |
[16] |
M. Christopher, A. Harrison and R. van Hoek, Creating the agile supply chain: Issues and
challenges, in Developments in Logistics and Supply Chain Management, Springer, (2016),
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[17] |
N. Costantino, M. Dotoli, M. Falagario, M. P. Fanti and A. M. Mangini,
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doi: 10.1016/j.ijpe.2011.08.021. |
[18] |
L. De Boer, E. Labro and P. Morlacchi,
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|
[19] |
G. W. Dickson,
An analysis of vendor selection systems and decisions, European Journal of Marketing, 2 (1996), 5-17.
doi: 10.1111/j.1745-493X.1966.tb00818.x. |
[20] |
D. Dubois and H. Prade,
The mean value of a fuzzy number, Fuzzy Sets and Systems, 24 (1987), 279-300.
doi: 10.1016/0165-0114(87)90028-5. |
[21] |
D. Dubois, E. Kerre, R. Mesiar and H. Prade, Fuzzy interval analysis, in Fundamentals of
Fuzzy Sets, Springer, 2000, 483–558. |
[22] |
E. A. Elsayed, A. Shaik Dawood and R. Karthikeyan, Evaluating alternatives through the application of topsis method with entropy weight International Journal of Engineering Trends and Technology (IJETT), 46 (2017).
doi: 10.14445/22315381/IJETT-V46P211. |
[23] |
H. Fargani, W. M. Cheung and R. Hasan, Ranking of factors that underlay the drivers of sustainable manufacturing based on their variation in a sample of UK manufacturing plants,
International Journal of Manufacturing Technology and Management (IJMTM), (2017). |
[24] |
S. Fayezi, A. Zutshi and A. O'Loughlin,
Understanding and development of supply chain agility and flexibility: A structured literature review, International Journal of Management Reviews, 19 (2017), 379-407.
doi: 10.1111/ijmr.12096. |
[25] |
M. Fazli-Khalaf, A. Mirzazadeh and M. S. Pishvaee,
A robust fuzzy stochastic programming model for the design of a reliable green closed-loop supply chain network, Human and Ecological Risk Assessment: An International Journal, 23 (2017), 2119-2149.
doi: 10.1080/10807039.2017.1367644. |
[26] |
P. Fortemps and M. Roubens,
Ranking and defuzzification methods based on area compensation, Fuzzy Sets and Systems, 82 (1996), 319-330.
doi: 10.1016/0165-0114(95)00273-1. |
[27] |
A. Ganguly, R. Nilchiani and J. V. Farr,
Evaluating agility in corporate enterprises, International Journal of Production Economics, 118 (2009), 410-423.
doi: 10.1016/j.ijpe.2008.12.009. |
[28] |
S. H. Ghodsypour and C. O'Brien,
A decision support system for supplier selection using an integrated analytic hierarchy process and linear programming, International Journal of Production Economics, 56/57 (1998), 199-212.
doi: 10.1016/S0925-5273(97)00009-1. |
[29] |
N. Gholamian, I. Mahdavi, R. Tavakkoli-Moghaddam and N. Mahdavi-Amiri,
Comprehensive fuzzy multi-objective multi-product multi-site aggregate production planning decisions in a supply chain under uncertainty, Applied Soft Computing, 37 (2015), 585-607.
doi: 10.1016/j.asoc.2015.08.041. |
[30] |
D. M. Gligor and M. C. Holcomb,
Understanding the role of logistics capabilities in achieving supply chain agility: A systematic literature review, Supply Chain Management: An International Journal, 17 (2012), 438-453.
doi: 10.1108/13598541211246594. |
[31] |
A. González,
A study of the ranking function approach through mean values, Fuzzy Sets and Systems, 35 (1990), 29-41.
doi: 10.1016/0165-0114(90)90016-Y. |
[32] |
D. Harrington,
Confirmatory Factor Analysis, Oxford University Press, 2009.
doi: 10.1093/acprof:oso/9780195339888.001.0001. |
[33] |
M. A. Hasan, J. Sarkis and R. Shankarr,
Agility and production flow layouts: An analytical decision analysis, Computers & Industrial Engineering, 62 (2012), 898-907.
doi: 10.1016/j.cie.2011.12.011. |
[34] |
A. Hasani, S. H. Zegordi and E. Nikbakhsh,
Robust closed-loop supply chain network design for perishable goods in agile manufacturing under uncertainty, International Journal of Production Research, 50 (2012), 4649-4669.
doi: 10.1080/00207543.2011.625051. |
[35] |
S. Heilpern,
The expected value of a fuzzy number, Fuzzy Sets and Systems, 47 (1992), 81-86.
doi: 10.1016/0165-0114(92)90062-9. |
[36] |
F. R. Jacobs, R. B. Chase and R. R. Lummus,
Operations and Supply Chain Management, McGraw-Hill/Irwin New York, 2014. |
[37] |
M. Jiménez, M. Arenas, A. Bilbao and M. V. Rodríguez,
Linear programming with fuzzy parameters: An interactive method resolution, European Journal of Operational Research, 177 (2007), 1599-1609.
doi: 10.1016/j.ejor.2005.10.002. |
[38] |
M. Jiménez,
Ranking fuzzy numbers through the comparison of its expected intervals, International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 4 (1996), 379-388.
doi: 10.1142/S0218488596000226. |
[39] |
T. Jitpaiboon,
The Roles of Information Systems Integration in the Supply Chain Integration Context-Firm Perspective, Ph. D thesis, University of Toledo, 2005. |
[40] |
I. T. Jolliffe and J. Cadima, Principal component analysis: A review and recent developments,
Phil. Trans. R. Soc. A, 374 (2016), 20150202. |
[41] |
D. Kannan,
Role of multiple stakeholders and the critical success factor theory for the sustainable supplier selection process, International Journal of Production Economics, 195 (2018), 391-418.
doi: 10.1016/j.ijpe.2017.02.020. |
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Row | Input attribute | Row | Input attribute |
1 | Number of facilities | 21 | Working hours |
2 | Staff training | 22 | Bureaucratic |
3 | Education managers | 23 | Defective products |
4 | Standard simple mentation in organizations | 24 | Material requirements planning |
5 | In Stock | 25 | Distribution plan |
6 | Product price | 26 | The geographical location of the factory |
7 | Product variety | 27 | The geographical area covered |
8 | Transportation | 28 | The political situation in the regions covered |
9 | Waste | 29 | Infrastructure |
10 | Market share | 30 | After Sales Service |
11 | Career Opportunities | 31 | Technical Support |
12 | The use of new technology | 32 | Management |
13 | Production Volume | 33 | Response to Customer Request |
14 | Automation | 34 | E-commerce Capability |
15 | Communication System | 35 | JIT |
16 | Delivery | 36 | Packing Ability |
17 | Time of preparation | 37 | Position in the industry |
18 | Lot Size | 38 | Product appearance |
19 | Work in process (WIP) | 39 | Quality |
20 | Specialist operators |
Row | Input attribute | Row | Input attribute |
1 | Number of facilities | 21 | Working hours |
2 | Staff training | 22 | Bureaucratic |
3 | Education managers | 23 | Defective products |
4 | Standard simple mentation in organizations | 24 | Material requirements planning |
5 | In Stock | 25 | Distribution plan |
6 | Product price | 26 | The geographical location of the factory |
7 | Product variety | 27 | The geographical area covered |
8 | Transportation | 28 | The political situation in the regions covered |
9 | Waste | 29 | Infrastructure |
10 | Market share | 30 | After Sales Service |
11 | Career Opportunities | 31 | Technical Support |
12 | The use of new technology | 32 | Management |
13 | Production Volume | 33 | Response to Customer Request |
14 | Automation | 34 | E-commerce Capability |
15 | Communication System | 35 | JIT |
16 | Delivery | 36 | Packing Ability |
17 | Time of preparation | 37 | Position in the industry |
18 | Lot Size | 38 | Product appearance |
19 | Work in process (WIP) | 39 | Quality |
20 | Specialist operators |
Input indicators | Row |
1 | Specialist operators |
2 | The use of new technology |
3 | Material requirements planning |
4 | Distribution plan |
5 | Response to Customer Request |
6 | Technical Support |
7 | E-commerce Capability |
8 | Product variety |
9 | Production Volume |
10 | Transportation |
11 | After Sales Service |
12 | Automation |
13 | Communication System |
14 | JIT |
15 | Quality |
16 | The geographical area covered |
Input indicators | Row |
1 | Specialist operators |
2 | The use of new technology |
3 | Material requirements planning |
4 | Distribution plan |
5 | Response to Customer Request |
6 | Technical Support |
7 | E-commerce Capability |
8 | Product variety |
9 | Production Volume |
10 | Transportation |
11 | After Sales Service |
12 | Automation |
13 | Communication System |
14 | JIT |
15 | Quality |
16 | The geographical area covered |
Output indicators | Row |
1 | Product price |
2 | Bureaucratic |
3 | Delivery time |
4 | Work in Process (WIP) |
Output indicators | Row |
1 | Product price |
2 | Bureaucratic |
3 | Delivery time |
4 | Work in Process (WIP) |
Component | Initial Eigenvalue | ||
Total | Percentage of Variance | Cumulative Percentage | |
1 | 2.074 | 12.965 | 12.965 |
2 | 1.803 | 11.267 | 24.232 |
3 | 1.575 | 9.843 | 34.075 |
4 | 1.380 | 8.625 | 42.700 |
5 | 1.334 | 8.336 | 51.036 |
6 | 1.181 | 7.383 | 58.419 |
7 | 1.027 | 6.418 | 64.836 |
8 | 0.935 | 5.841 | 70.677 |
9 | 0.884 | 5.523 | 76.200 |
10 | 0.793 | 4.959 | 81.159 |
11 | 0.720 | 4.498 | 85.656 |
12 | 0.624 | 3.898 | 89.554 |
13 | 0.580 | 3.624 | 93.178 |
14 | 0.423 | 2.642 | 95.820 |
15 | 0.362 | 2.265 | 98.086 |
16 | 0.306 | 1.914 | 100.000 |
Component | Initial Eigenvalue | ||
Total | Percentage of Variance | Cumulative Percentage | |
1 | 2.074 | 12.965 | 12.965 |
2 | 1.803 | 11.267 | 24.232 |
3 | 1.575 | 9.843 | 34.075 |
4 | 1.380 | 8.625 | 42.700 |
5 | 1.334 | 8.336 | 51.036 |
6 | 1.181 | 7.383 | 58.419 |
7 | 1.027 | 6.418 | 64.836 |
8 | 0.935 | 5.841 | 70.677 |
9 | 0.884 | 5.523 | 76.200 |
10 | 0.793 | 4.959 | 81.159 |
11 | 0.720 | 4.498 | 85.656 |
12 | 0.624 | 3.898 | 89.554 |
13 | 0.580 | 3.624 | 93.178 |
14 | 0.423 | 2.642 | 95.820 |
15 | 0.362 | 2.265 | 98.086 |
16 | 0.306 | 1.914 | 100.000 |
Component | Extraction Sums of Squared Loadings | Rotation Sums of Squared Loadings | ||||
Total | Percentage of Variance | Cumulative Percentage | Total | Percentage of Variance | Cumulative Percentage | |
1 | 2.074 | 12.965 | 12.965 | 1.548 | 9.675 | 9.675 |
2 | 1.803 | 11.267 | 24.232 | 1.547 | 9.672 | 19.347 |
3 | 1.575 | 9.843 | 34.075 | 1.510 | 9.440 | 28.787 |
4 | 1.380 | 8.625 | 42.700 | 1.506 | 9.410 | 38.197 |
5 | 1.334 | 8.336 | 51.036 | 1.460 | 9.126 | 47.324 |
6 | 1.181 | 7.383 | 58.419 | 1.401 | 8.757 | 56.081 |
7 | 1.027 | 6.418 | 64.836 | 1.401 | 8.755 | 64.836 |
Component | Extraction Sums of Squared Loadings | Rotation Sums of Squared Loadings | ||||
Total | Percentage of Variance | Cumulative Percentage | Total | Percentage of Variance | Cumulative Percentage | |
1 | 2.074 | 12.965 | 12.965 | 1.548 | 9.675 | 9.675 |
2 | 1.803 | 11.267 | 24.232 | 1.547 | 9.672 | 19.347 |
3 | 1.575 | 9.843 | 34.075 | 1.510 | 9.440 | 28.787 |
4 | 1.380 | 8.625 | 42.700 | 1.506 | 9.410 | 38.197 |
5 | 1.334 | 8.336 | 51.036 | 1.460 | 9.126 | 47.324 |
6 | 1.181 | 7.383 | 58.419 | 1.401 | 8.757 | 56.081 |
7 | 1.027 | 6.418 | 64.836 | 1.401 | 8.755 | 64.836 |
Variables | Components | ||||||
1 | 2 | 3 | 4 | 5 | 6 | 7 | |
X1 | 0.042 | -0.192 | 0.615 | -0.211 | 0.159 | -0.273 | -0.029 |
X2 | -0.175 | 0.176 | -0.015 | -0.065 | -0.709 | -0.101 | -0.061 |
X3 | -0.083 | -0.096 | -0.145 | 0.479 | -0.440 | 0.219 | -0.067 |
X4 | 0.120 | 0.177 | -0.220 | 0.609 | 0.221 | -0.251 | -0.108 |
X5 | -0.208 | -0.827 | 0.065 | 0.139 | 0.048 | 0.263 | 0.109 |
X6 | -0.223 | 0.571 | -0.207 | 0.099 | 0.256 | 0.182 | 0.418 |
X7 | 0.133 | -0.134 | 0.205 | 0.753 | -0.070 | 0.073 | 0.037 |
X8 | -0.073 | 0.004 | -0.090 | -0.018 | -0.016 | -0.729 | -0.123 |
X9 | 0.841 | 0.035 | 0.135 | 0.022 | 0.083 | -0.011 | 0.014 |
X10 | 0.551 | -0.016 | -0.100 | 0.309 | -0.035 | 0.370 | -0.010 |
X11 | -0.110 | 0.228 | 0.695 | 0.221 | 0.190 | 0.141 | -0.097 |
X12 | -0.258 | 0.541 | 0.155 | 0.034 | -0.283 | 0.292 | 0.244 |
X13 | 0.175 | -0.166 | -0.147 | -0.281 | 0.151 | 0.506 | -0.591 |
X14 | -0.177 | 0.115 | -0.637 | 0.014 | 0.262 | -0.176 | -0.120 |
X15 | -0.464 | 0.159 | 0.031 | -0.086 | 0.629 | -0.029 | -0.048 |
X16 | 0.111 | 0.005 | -0.030 | -0.163 | 0.072 | 0.191 | 0.861 |
Variables | Components | ||||||
1 | 2 | 3 | 4 | 5 | 6 | 7 | |
X1 | 0.042 | -0.192 | 0.615 | -0.211 | 0.159 | -0.273 | -0.029 |
X2 | -0.175 | 0.176 | -0.015 | -0.065 | -0.709 | -0.101 | -0.061 |
X3 | -0.083 | -0.096 | -0.145 | 0.479 | -0.440 | 0.219 | -0.067 |
X4 | 0.120 | 0.177 | -0.220 | 0.609 | 0.221 | -0.251 | -0.108 |
X5 | -0.208 | -0.827 | 0.065 | 0.139 | 0.048 | 0.263 | 0.109 |
X6 | -0.223 | 0.571 | -0.207 | 0.099 | 0.256 | 0.182 | 0.418 |
X7 | 0.133 | -0.134 | 0.205 | 0.753 | -0.070 | 0.073 | 0.037 |
X8 | -0.073 | 0.004 | -0.090 | -0.018 | -0.016 | -0.729 | -0.123 |
X9 | 0.841 | 0.035 | 0.135 | 0.022 | 0.083 | -0.011 | 0.014 |
X10 | 0.551 | -0.016 | -0.100 | 0.309 | -0.035 | 0.370 | -0.010 |
X11 | -0.110 | 0.228 | 0.695 | 0.221 | 0.190 | 0.141 | -0.097 |
X12 | -0.258 | 0.541 | 0.155 | 0.034 | -0.283 | 0.292 | 0.244 |
X13 | 0.175 | -0.166 | -0.147 | -0.281 | 0.151 | 0.506 | -0.591 |
X14 | -0.177 | 0.115 | -0.637 | 0.014 | 0.262 | -0.176 | -0.120 |
X15 | -0.464 | 0.159 | 0.031 | -0.086 | 0.629 | -0.029 | -0.048 |
X16 | 0.111 | 0.005 | -0.030 | -0.163 | 0.072 | 0.191 | 0.861 |
Supplier | Score | Supplier | Score | Supplier | Score | Supplier | Score |
1 | -0.44143 | 16 | -0.45093 | 31 | -0.70673 | 46 | 0.22046 |
2 | -0.39948 | 17 | -0.16193 | 32 | 0.52357 | 47 | 0.646209 |
3 | 0.079517 | 18 | 0.41908 | 33 | 0.574339 | 48 | -0.2407 |
4 | -0.01854 | 19 | -0.05046 | 34 | 0.054961 | 49 | 0.430716 |
5 | 0.06819 | 20 | 0.010264 | 35 | -0.3108 | 50 | 0.175306 |
6 | -0.16339 | 21 | -0.29805 | 36 | -0.29681 | 51 | -0.12202 |
7 | -0.47472 | 22 | 0.283236 | 37 | 0.379933 | 52 | 0.065461 |
8 | -0.26409 | 23 | -0.10214 | 38 | 0.083386 | 53 | -0.80726 |
9 | 0.359434 | 24 | -0.3874 | 39 | -0.11785 | 54 | -0.19505 |
10 | -0.48728 | 25 | 0.278027 | 40 | 0.092893 | 55 | 0.258526 |
11 | 0.044161 | 26 | 0.196247 | 41 | -0.19233 | 56 | 0.570286 |
12 | 0.50004 | 27 | 0.194767 | 42 | 0.121639 | 57 | 0.265066 |
13 | 1.064131 | 28 | 0.009783 | 43 | -0.39538 | 58 | 0.098087 |
14 | -0.72305 | 29 | -0.08439 | 44 | 0.676464 | 59 | -0.50213 |
15 | -0.19635 | 30 | 0.266653 | 45 | -0.02721 | 60 | -0.39293 |
Supplier | Score | Supplier | Score | Supplier | Score | Supplier | Score |
1 | -0.44143 | 16 | -0.45093 | 31 | -0.70673 | 46 | 0.22046 |
2 | -0.39948 | 17 | -0.16193 | 32 | 0.52357 | 47 | 0.646209 |
3 | 0.079517 | 18 | 0.41908 | 33 | 0.574339 | 48 | -0.2407 |
4 | -0.01854 | 19 | -0.05046 | 34 | 0.054961 | 49 | 0.430716 |
5 | 0.06819 | 20 | 0.010264 | 35 | -0.3108 | 50 | 0.175306 |
6 | -0.16339 | 21 | -0.29805 | 36 | -0.29681 | 51 | -0.12202 |
7 | -0.47472 | 22 | 0.283236 | 37 | 0.379933 | 52 | 0.065461 |
8 | -0.26409 | 23 | -0.10214 | 38 | 0.083386 | 53 | -0.80726 |
9 | 0.359434 | 24 | -0.3874 | 39 | -0.11785 | 54 | -0.19505 |
10 | -0.48728 | 25 | 0.278027 | 40 | 0.092893 | 55 | 0.258526 |
11 | 0.044161 | 26 | 0.196247 | 41 | -0.19233 | 56 | 0.570286 |
12 | 0.50004 | 27 | 0.194767 | 42 | 0.121639 | 57 | 0.265066 |
13 | 1.064131 | 28 | 0.009783 | 43 | -0.39538 | 58 | 0.098087 |
14 | -0.72305 | 29 | -0.08439 | 44 | 0.676464 | 59 | -0.50213 |
15 | -0.19635 | 30 | 0.266653 | 45 | -0.02721 | 60 | -0.39293 |
Parameter | Value | Parameter | Value |
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r1 | r2 | r3 | Problem No. | Obj1 | Obj2 | Obj3 | CPU time (Sec) |
1 | 0 | 0 | 1 | 3.69E+11 | 1.38E+08 | 0.00E+00 | 134 |
2 | 3.82E+12 | 1.26E+09 | 0.00E+00 | 646 | |||
0 | 1 | 0 | 1 | 6.61E+12 | 2.44E+07 | 0.00E+00 | 164 |
2 | 2.50E+15 | 2.53E+08 | 0.00E+00 | 655 | |||
0 | 0 | 1 | 1 | 6.61E+12 | 1.38E+08 | 7.46E+07 | 132 |
2 | 2.50E+15 | 1.26E+09 | 3.74E+11 | 692 | |||
0.45 | 0.45 | 0.1 | 1 | 3.39E+12 | 7.89E+07 | 1.42E+07 | 210 |
2 | 1.13E+15 | 6.58E+08 | 8.33E+10 | 512 | |||
0.35 | 0.35 | 0.3 | 1 | 3.99E+12 | 9.30E+07 | 2.76E+07 | 167 |
2 | 1.30E+15 | 7.29E+08 | 1.46E+11 | 472 | |||
0.25 | 0.25 | 0.5 | 1 | 4.55E+12 | 1.06E+08 | 4.70E+07 | 173 |
2 | 1.58E+15 | 9.41E+08 | 2.31E+11 | 627 | |||
0.15 | 0.15 | 0.7 | 1 | 5.50E+12 | 1.16E+08 | 5.67E+07 | 159 |
2 | 1.80E+15 | 9.91E+08 | 3.07E+11 | 679 | |||
0.05 | 0.05 | 0.9 | 1 | 6.20E+12 | 1.25E+08 | 7.02E+07 | 134 |
2 | 2.25E+15 | 1.13E+09 | 3.48E+11 | 646 | |||
0.2 | 0.3 | 0.5 | 1 | 5.20E+12 | 9.83E+07 | 4.78E+07 | 164 |
2 | 1.68E+15 | 8.90E+08 | 2.25E+11 | 655 | |||
0.2 | 0.5 | 0.3 | 1 | 4.93E+12 | 7.21E+07 | 2.76E+07 | 132 |
2 | 1.70E+15 | 6.48E+08 | 1.23E+11 | 690 | |||
0.3 | 0.2 | 0.5 | 1 | 4.38E+12 | 1.13E+08 | 4.63E+07 | 210 |
2 | 1.53E+15 | 9.81E+08 | 2.31E+11 | 512 | |||
0.3 | 0.5 | 0.2 | 1 | 4.24E+12 | 6.65E+07 | 1.72E+07 | 167 |
2 | 1.53E+15 | 6.38E+08 | 8.61E+10 | 472 | |||
0.5 | 0.2 | 0.3 | 1 | 3.12E+12 | 1.08E+08 | 2.84E+07 | 173 |
2 | 9.27E+14 | 9.84E+08 | 1.12E+11 | 627 | |||
0.5 | 0.3 | 0.2 | 1 | 2.93E+12 | 9.59E+07 | 1.79E+07 | 159 |
2 | 9.47E+14 | 8.90E+08 | 9.36E+10 | 679 |
r1 | r2 | r3 | Problem No. | Obj1 | Obj2 | Obj3 | CPU time (Sec) |
1 | 0 | 0 | 1 | 3.69E+11 | 1.38E+08 | 0.00E+00 | 134 |
2 | 3.82E+12 | 1.26E+09 | 0.00E+00 | 646 | |||
0 | 1 | 0 | 1 | 6.61E+12 | 2.44E+07 | 0.00E+00 | 164 |
2 | 2.50E+15 | 2.53E+08 | 0.00E+00 | 655 | |||
0 | 0 | 1 | 1 | 6.61E+12 | 1.38E+08 | 7.46E+07 | 132 |
2 | 2.50E+15 | 1.26E+09 | 3.74E+11 | 692 | |||
0.45 | 0.45 | 0.1 | 1 | 3.39E+12 | 7.89E+07 | 1.42E+07 | 210 |
2 | 1.13E+15 | 6.58E+08 | 8.33E+10 | 512 | |||
0.35 | 0.35 | 0.3 | 1 | 3.99E+12 | 9.30E+07 | 2.76E+07 | 167 |
2 | 1.30E+15 | 7.29E+08 | 1.46E+11 | 472 | |||
0.25 | 0.25 | 0.5 | 1 | 4.55E+12 | 1.06E+08 | 4.70E+07 | 173 |
2 | 1.58E+15 | 9.41E+08 | 2.31E+11 | 627 | |||
0.15 | 0.15 | 0.7 | 1 | 5.50E+12 | 1.16E+08 | 5.67E+07 | 159 |
2 | 1.80E+15 | 9.91E+08 | 3.07E+11 | 679 | |||
0.05 | 0.05 | 0.9 | 1 | 6.20E+12 | 1.25E+08 | 7.02E+07 | 134 |
2 | 2.25E+15 | 1.13E+09 | 3.48E+11 | 646 | |||
0.2 | 0.3 | 0.5 | 1 | 5.20E+12 | 9.83E+07 | 4.78E+07 | 164 |
2 | 1.68E+15 | 8.90E+08 | 2.25E+11 | 655 | |||
0.2 | 0.5 | 0.3 | 1 | 4.93E+12 | 7.21E+07 | 2.76E+07 | 132 |
2 | 1.70E+15 | 6.48E+08 | 1.23E+11 | 690 | |||
0.3 | 0.2 | 0.5 | 1 | 4.38E+12 | 1.13E+08 | 4.63E+07 | 210 |
2 | 1.53E+15 | 9.81E+08 | 2.31E+11 | 512 | |||
0.3 | 0.5 | 0.2 | 1 | 4.24E+12 | 6.65E+07 | 1.72E+07 | 167 |
2 | 1.53E+15 | 6.38E+08 | 8.61E+10 | 472 | |||
0.5 | 0.2 | 0.3 | 1 | 3.12E+12 | 1.08E+08 | 2.84E+07 | 173 |
2 | 9.27E+14 | 9.84E+08 | 1.12E+11 | 627 | |||
0.5 | 0.3 | 0.2 | 1 | 2.93E+12 | 9.59E+07 | 1.79E+07 | 159 |
2 | 9.47E+14 | 8.90E+08 | 9.36E+10 | 679 |
Index | Razmi et al. (2011) | Yauch (2011) | Ghodsypour and O'Brien (1998) | Min and Shin (2008) | Weber et al. (1991) | Abratt and Kleyn (2012) | Dickson (1996) | Prater et al. (2001) | Kassaee et al. (2014) | Dahmardeh et al. (2010) | Kumar et al. (2011) | Aktepe et al. (1999) | Lin (2009) | Chan and Thong (2009) | This study |
1 | * | * | * | * | * | * | * | * | * | * | |||||
2 | * | * | * | * | * | * | * | * | * | ||||||
3 | * | * | * | * | * | * | * | * | * | ||||||
4 | * | * | * | * | * | * | * | * | * | ||||||
5 | * | * | * | * | |||||||||||
6 | * | * | * | * | * | * | * | * | * | * | * | * | * | ||
7 | * | * | * | * | * | * | * | * | * | ||||||
8 | * | * | * | * | |||||||||||
9 | * | * | * | * | * | * | * | * | * | ||||||
10 | * | * | * | * | * | * | * | * | |||||||
11 | * | * | * | * | * | * | * | * | |||||||
12 | * | * | * | * | * | * | * | * | * | * | |||||
13 | * | * | * | * | * | * | * | * | * | ||||||
14 | * | * | * | * | * | * | * | * | * | ||||||
15 | * | * | * | * | * | * | * | * | * | * | * | * | |||
16 | * | * | * | * | * | * | * | * | * | * | |||||
17 | * | * | * | * | * | * | * | * | |||||||
18 | * | * | * | * | * | * | * | * | * | ||||||
19 | * | * | * | * | * | * | * | * | * | ||||||
20 | * | * | * | * | * | * | * | * | |||||||
21 | * | * | * | * | * | * | * | * | |||||||
22 | * | * | * | * | * | * | * | * | * | ||||||
23 | * | * | * | * | * | * | * | * | * | ||||||
24 | * | * | * | * | * | * | * | * | * | ||||||
25 | * | * | * | ||||||||||||
26 | * | * | * | * | * | * | * | ||||||||
27 | * | * | * | * | * | * | * | ||||||||
28 | * | * | * | * | |||||||||||
29 | * | ||||||||||||||
30 | * | * | * | * | * | * | * | * | * | * | * | * | |||
31 | * | * | * | * | * | * | * | * | * | * | * | * | |||
32 | * | * | * | * | * | * | * | * | |||||||
33 | * | * | * | * | * | * | * | * | |||||||
34 | * | * | * | * | * | * | * | * | |||||||
35 | |||||||||||||||
36 | * | * | * | * | * | * | * | * | * | ||||||
37 | * | * | * | * | * | * | * | * | * | * | * | * | |||
38 | * | * | * | * | * | * | * | * | * | ||||||
39 | * | * | * | * | * | * | * | * | * | * | * | * | * |
Index | Razmi et al. (2011) | Yauch (2011) | Ghodsypour and O'Brien (1998) | Min and Shin (2008) | Weber et al. (1991) | Abratt and Kleyn (2012) | Dickson (1996) | Prater et al. (2001) | Kassaee et al. (2014) | Dahmardeh et al. (2010) | Kumar et al. (2011) | Aktepe et al. (1999) | Lin (2009) | Chan and Thong (2009) | This study |
1 | * | * | * | * | * | * | * | * | * | * | |||||
2 | * | * | * | * | * | * | * | * | * | ||||||
3 | * | * | * | * | * | * | * | * | * | ||||||
4 | * | * | * | * | * | * | * | * | * | ||||||
5 | * | * | * | * | |||||||||||
6 | * | * | * | * | * | * | * | * | * | * | * | * | * | ||
7 | * | * | * | * | * | * | * | * | * | ||||||
8 | * | * | * | * | |||||||||||
9 | * | * | * | * | * | * | * | * | * | ||||||
10 | * | * | * | * | * | * | * | * | |||||||
11 | * | * | * | * | * | * | * | * | |||||||
12 | * | * | * | * | * | * | * | * | * | * | |||||
13 | * | * | * | * | * | * | * | * | * | ||||||
14 | * | * | * | * | * | * | * | * | * | ||||||
15 | * | * | * | * | * | * | * | * | * | * | * | * | |||
16 | * | * | * | * | * | * | * | * | * | * | |||||
17 | * | * | * | * | * | * | * | * | |||||||
18 | * | * | * | * | * | * | * | * | * | ||||||
19 | * | * | * | * | * | * | * | * | * | ||||||
20 | * | * | * | * | * | * | * | * | |||||||
21 | * | * | * | * | * | * | * | * | |||||||
22 | * | * | * | * | * | * | * | * | * | ||||||
23 | * | * | * | * | * | * | * | * | * | ||||||
24 | * | * | * | * | * | * | * | * | * | ||||||
25 | * | * | * | ||||||||||||
26 | * | * | * | * | * | * | * | ||||||||
27 | * | * | * | * | * | * | * | ||||||||
28 | * | * | * | * | |||||||||||
29 | * | ||||||||||||||
30 | * | * | * | * | * | * | * | * | * | * | * | * | |||
31 | * | * | * | * | * | * | * | * | * | * | * | * | |||
32 | * | * | * | * | * | * | * | * | |||||||
33 | * | * | * | * | * | * | * | * | |||||||
34 | * | * | * | * | * | * | * | * | |||||||
35 | |||||||||||||||
36 | * | * | * | * | * | * | * | * | * | ||||||
37 | * | * | * | * | * | * | * | * | * | * | * | * | |||
38 | * | * | * | * | * | * | * | * | * | ||||||
39 | * | * | * | * | * | * | * | * | * | * | * | * | * |
No. | In1 | In2 | In3 | In4 | In5 | In6 | In7 | In8 | In9 | In10 | In11 | In12 | In13 | In14 | In15 | In16 |
1 | 0.54 | 0.82 | 0.5 | 0.62 | 0.75 | 0.45 | 0.62 | 0.64 | 0.71 | 0.6 | 0.5 | 0.57 | 0.52 | 0.35 | 0.23 | 0.6 |
2 | 0.5 | 0.04 | 0.63 | 0.63 | 0.95 | 0.46 | 0.6 | 0.76 | 0.4 | 0.77 | 0.5 | 0.6 | 0.8 | 0.53 | 0.38 | 0.47 |
3 | 0.27 | 0.66 | 0.72 | 0.97 | 0.93 | 0.48 | 0.78 | 0.12 | 0.37 | 0.78 | 0.68 | 0.63 | 0.8 | 0.35 | 0.12 | 0.33 |
4 | 0.43 | 0.34 | 0.71 | 0.75 | 0.92 | 0.56 | 0.72 | 0.44 | 0.53 | 0.68 | 0.64 | 0.68 | 0.72 | 0.37 | 0.32 | 0.3 |
5 | 0.72 | 0.13 | 0.54 | 0.73 | 0.68 | 0.5 | 0.52 | 0.65 | 0.71 | 0.79 | 0.62 | 0.61 | 0.54 | 0.55 | 0.19 | 0.35 |
6 | 0.71 | 0.45 | 0.81 | 0.52 | 0.9 | 0.52 | 0.55 | 0.02 | 0.31 | 0.72 | 0.7 | 0.65 | 0.7 | 0.34 | 0.1 | 0.34 |
7 | 0.5 | 0.43 | 0.89 | 0.94 | 0.85 | 0.41 | 0.58 | 0.5 | 0.58 | 0.61 | 0.63 | 0.53 | 0.76 | 0.52 | 0.76 | 0.34 |
8 | 0.34 | 0.77 | 0.74 | 0.55 | 0.74 | 0.42 | 0.7 | 0.06 | 0.8 | 0.76 | 0.4 | 0.63 | 0.79 | 0.44 | 0.24 | 0.49 |
9 | 0.52 | 0.29 | 0.86 | 0.57 | 0.73 | 0.62 | 0.59 | 0.31 | 0.71 | 0.71 | 0.65 | 0.65 | 0.77 | 0.46 | 0.74 | 0.69 |
10 | 0.39 | 0.58 | 0.65 | 0.76 | 0.67 | 0.66 | 0.62 | 0.4 | 0.21 | 0.61 | 0.42 | 0.6 | 0.52 | 0.56 | 0.94 | 0.36 |
11 | 0.4 | 0.53 | 0.97 | 0.81 | 0.96 | 0.47 | 0.76 | 0.17 | 0.69 | 0.77 | 0.42 | 0.74 | 0.67 | 0.24 | 0.24 | 0.51 |
12 | 0.58 | 0.07 | 0.75 | 0.54 | 0.65 | 0.6 | 0.53 | 0.1 | 0.86 | 0.72 | 0.63 | 0.74 | 0.7 | 0.3 | 0.06 | 0.55 |
13 | 0.4 | 0.12 | 0.62 | 0.87 | 0.62 | 0.7 | 0.73 | 0.04 | 0.62 | 0.79 | 0.6 | 0.8 | 0.79 | 0.21 | 0.59 | 0.64 |
14 | 0.34 | 0.81 | 0.87 | 0.86 | 0.63 | 0.67 | 0.52 | 0.94 | 0.2 | 0.73 | 0.49 | 0.52 | 0.77 | 0.5 | 0.22 | 0.32 |
15 | 0.8 | 0.73 | 0.89 | 0.5 | 0.8 | 0.59 | 0.58 | 0.94 | 0.26 | 0.74 | 0.65 | 0.62 | 0.57 | 0.1 | 0.44 | 0.52 |
16 | 0.62 | 0.27 | 0.57 | 0.89 | 1.00 | 0.44 | 0.7 | 0.67 | 0.2 | 0.62 | 0.44 | 0.56 | 0.59 | 0.41 | 0.86 | 0.65 |
17 | 0.26 | 0.01 | 0.86 | 0.71 | 0.91 | 0.51 | 0.54 | 0.61 | 0.37 | 0.8 | 0.42 | 0.64 | 0.65 | 0.29 | 0.37 | 0.66 |
18 | 0.33 | 0.63 | 0.96 | 0.93 | 0.61 | 0.65 | 0.73 | 0.23 | 0.44 | 0.71 | 0.7 | 0.64 | 0.54 | 0.52 | 0.17 | 0.63 |
19 | 0.5 | 0.54 | 0.91 | 0.86 | 0.86 | 0.53 | 0.74 | 0.61 | 0.65 | 0.71 | 0.57 | 0.61 | 0.74 | 0.55 | 0.94 | 0.48 |
21 | 0.33 | 0.89 | 0.68 | 0.62 | 0.81 | 0.59 | 0.51 | 0.38 | 0.51 | 0.75 | 0.51 | 0.77 | 0.79 | 0.41 | 0.86 | 0.35 |
22 | 0.61 | 0.4 | 0.56 | 0.54 | 0.83 | 0.7 | 0.53 | 0.37 | 0.63 | 0.7 | 0.56 | 0.64 | 0.58 | 0.33 | 0.97 | 0.67 |
23 | 0.68 | 0.84 | 0.98 | 0.9 | 0.88 | 0.44 | 0.69 | 0.03 | 0.6 | 0.74 | 0.43 | 0.59 | 0.72 | 0.14 | 0.25 | 0.61 |
24 | 0.41 | 0.81 | 0.81 | 0.95 | 0.73 | 0.46 | 0.77 | 0.66 | 0.5 | 0.68 | 0.47 | 0.63 | 0.69 | 0.23 | 0.31 | 0.3 |
25 | 0.27 | 0.44 | 0.63 | 0.55 | 0.94 | 0.69 | 0.72 | 0.18 | 0.28 | 0.74 | 0.61 | 0.71 | 0.58 | 0.21 | 0.00 | 0.59 |
26 | 0.28 | 0.37 | 0.53 | 0.55 | 0.85 | 0.47 | 0.68 | 0.33 | 0.75 | 0.78 | 0.46 | 0.65 | 0.67 | 0.18 | 0.35 | 0.7 |
27 | 0.64 | 0.79 | 0.63 | 0.7 | 0.89 | 0.45 | 0.57 | 0.15 | 0.69 | 0.77 | 0.66 | 0.71 | 0.65 | 0.25 | 0.55 | 0.52 |
28 | 0.31 | 0.89 | 0.99 | 0.62 | 0.67 | 0.6 | 0.79 | 0.25 | 0.38 | 0.72 | 0.51 | 0.8 | 0.54 | 0.39 | 0.11 | 0.55 |
29 | 0.6 | 0.02 | 0.76 | 0.73 | 0.64 | 0.7 | 0.5 | 0.67 | 0.53 | 0.64 | 0.42 | 0.79 | 0.62 | 0.45 | 0.99 | 0.36 |
30 | 0.42 | 0.23 | 0.76 | 0.9 | 0.81 | 0.66 | 0.79 | 0.96 | 0.69 | 0.78 | 0.56 | 0.51 | 0.76 | 0.2 | 0.51 | 0.36 |
31 | 0.8 | 0.48 | 0.8 | 0.51 | 0.83 | 0.43 | 0.66 | 0.84 | 0.3 | 0.78 | 0.48 | 0.58 | 0.69 | 0.48 | 0.12 | 0.31 |
32 | 0.58 | 0.05 | 0.66 | 0.6 | 0.73 | 0.61 | 0.73 | 0.23 | 0.87 | 0.74 | 0.49 | 0.67 | 0.77 | 0.32 | 0.03 | 0.68 |
33 | 0.57 | 0.21 | 0.86 | 0.71 | 0.64 | 0.54 | 0.78 | 0.45 | 0.55 | 0.74 | 0.68 | 0.77 | 0.56 | 0.31 | 0.99 | 0.41 |
34 | 0.76 | 0.63 | 0.65 | 0.93 | 0.66 | 0.44 | 0.68 | 0.99 | 0.75 | 0.72 | 0.52 | 0.8 | 0.5 | 0.2 | 0.5 | 0.38 |
35 | 0.28 | 0.04 | 0.71 | 0.67 | 0.72 | 0.43 | 0.57 | 0.44 | 0.72 | 0.71 | 0.45 | 0.5 | 0.75 | 0.41 | 0.29 | 0.47 |
36 | 0.45 | 0.75 | 0.87 | 0.7 | 0.62 | 0.41 | 0.57 | 0.92 | 0.63 | 0.73 | 0.62 | 0.78 | 0.67 | 0.34 | 0.36 | 0.35 |
37 | 0.73 | 0.1 | 0.75 | 0.98 | 0.73 | 0.55 | 0.56 | 0.34 | 0.75 | 0.69 | 0.62 | 0.52 | 0.73 | 0.23 | 0.61 | 0.57 |
38 | 0.75 | 0.2 | 0.75 | 0.72 | 0.95 | 0.51 | 0.67 | 0.72 | 0.46 | 0.72 | 0.66 | 0.66 | 0.75 | 0.49 | 0.91 | 0.58 |
39 | 0.8 | 0.98 | 0.52 | 0.86 | 0.86 | 0.68 | 0.5 | 0.31 | 0.69 | 0.65 | 0.63 | 0.64 | 0.76 | 0.17 | 0.27 | 0.43 |
41 | 0.33 | 0.44 | 0.84 | 0.84 | 0.68 | 0.7 | 0.58 | 0.98 | 0.37 | 0.6 | 0.5 | 0.78 | 0.54 | 0.52 | 0.27 | 0.7 |
42 | 0.66 | 0.97 | 0.59 | 0.7 | 0.78 | 0.59 | 0.77 | 0.72 | 0.44 | 0.68 | 0.67 | 0.71 | 0.66 | 0.16 | 0.34 | 0.54 |
43 | 0.32 | 0.72 | 0.75 | 0.58 | 0.73 | 0.58 | 0.56 | 0.26 | 0.21 | 0.62 | 0.51 | 0.66 | 0.78 | 0.28 | 0.62 | 0.62 |
44 | 0.52 | 0.17 | 0.56 | 0.99 | 0.76 | 0.65 | 0.77 | 0.59 | 0.46 | 0.73 | 0.67 | 0.67 | 0.5 | 0.41 | 0.87 | 0.56 |
45 | 0.59 | 0.53 | 0.8 | 0.78 | 0.93 | 0.46 | 0.71 | 0.07 | 0.78 | 0.66 | 0.52 | 0.59 | 0.68 | 0.16 | 0.71 | 0.36 |
46 | 0.46 | 0.01 | 0.77 | 0.77 | 0.99 | 0.5 | 0.71 | 0.76 | 0.9 | 0.78 | 0.59 | 0.6 | 0.79 | 0.48 | 0.46 | 0.54 |
47 | 0.79 | 0.07 | 0.82 | 0.68 | 0.81 | 0.59 | 0.74 | 0.3 | 0.64 | 0.75 | 0.65 | 0.62 | 0.72 | 0.12 | 0.41 | 0.6 |
48 | 0.41 | 0.18 | 0.64 | 0.59 | 0.79 | 0.46 | 0.73 | 0.89 | 0.76 | 0.64 | 0.62 | 0.54 | 0.58 | 0.53 | 0.22 | 0.41 |
49 | 0.45 | 0.09 | 0.53 | 0.86 | 0.65 | 0.64 | 0.74 | 0.27 | 0.28 | 0.77 | 0.62 | 0.58 | 0.71 | 0.46 | 0.84 | 0.4 |
50 | 0.4 | 0.49 | 0.91 | 0.62 | 0.88 | 0.58 | 0.75 | 0.39 | 0.35 | 0.71 | 0.65 | 0.78 | 0.64 | 0.13 | 0.39 | 0.44 |
51 | 0.66 | 0.47 | 0.71 | 0.61 | 0.67 | 0.57 | 0.66 | 0.02 | 0.31 | 0.6 | 0.61 | 0.75 | 0.76 | 0.51 | 0.69 | 0.35 |
52 | 0.62 | 0.42 | 0.81 | 0.54 | 0.93 | 0.54 | 0.52 | 0.11 | 0.22 | 0.69 | 0.68 | 0.79 | 0.62 | 0.35 | 0.55 | 0.69 |
53 | 0.7 | 0.93 | 0.66 | 0.52 | 0.9 | 0.45 | 0.57 | 0.65 | 0.31 | 0.64 | 0.56 | 0.58 | 0.8 | 0.23 | 0.25 | 0.43 |
54 | 0.25 | 0.91 | 0.82 | 0.99 | 0.63 | 0.65 | 0.58 | 0.88 | 0.36 | 0.76 | 0.46 | 0.78 | 0.64 | 0.52 | 0.17 | 0.62 |
55 | 0.28 | 0.37 | 0.52 | 0.55 | 0.69 | 0.6 | 0.65 | 0.63 | 0.28 | 0.63 | 0.7 | 0.72 | 0.62 | 0.15 | 0.88 | 0.67 |
56 | 0.64 | 0.42 | 1.00 | 1.00 | 0.91 | 0.69 | 0.71 | 0.11 | 0.89 | 0.77 | 0.51 | 0.62 | 0.56 | 0.42 | 0.21 | 0.63 |
57 | 0.49 | 0.63 | 0.91 | 0.82 | 0.84 | 0.54 | 0.8 | 0.01 | 0.53 | 0.79 | 0.62 | 0.56 | 0.52 | 0.48 | 0.19 | 0.49 |
58 | 0.49 | 0.97 | 0.56 | 0.7 | 0.6 | 0.66 | 0.58 | 0.26 | 0.82 | 0.8 | 0.42 | 0.61 | 0.77 | 0.46 | 0.59 | 0.56 |
59 | 0.71 | 0.09 | 0.62 | 0.5 | 0.79 | 0.52 | 0.67 | 0.59 | 0.21 | 0.66 | 0.44 | 0.51 | 0.73 | 0.29 | 0.6 | 0.4 |
60 | 0.27 | 0.06 | 0.97 | 0.68 | 0.98 | 0.59 | 0.58 | 0.25 | 0.2 | 0.69 | 0.4 | 0.75 | 0.68 | 0.54 | 0.72 | 0.49 |
No. | In1 | In2 | In3 | In4 | In5 | In6 | In7 | In8 | In9 | In10 | In11 | In12 | In13 | In14 | In15 | In16 |
1 | 0.54 | 0.82 | 0.5 | 0.62 | 0.75 | 0.45 | 0.62 | 0.64 | 0.71 | 0.6 | 0.5 | 0.57 | 0.52 | 0.35 | 0.23 | 0.6 |
2 | 0.5 | 0.04 | 0.63 | 0.63 | 0.95 | 0.46 | 0.6 | 0.76 | 0.4 | 0.77 | 0.5 | 0.6 | 0.8 | 0.53 | 0.38 | 0.47 |
3 | 0.27 | 0.66 | 0.72 | 0.97 | 0.93 | 0.48 | 0.78 | 0.12 | 0.37 | 0.78 | 0.68 | 0.63 | 0.8 | 0.35 | 0.12 | 0.33 |
4 | 0.43 | 0.34 | 0.71 | 0.75 | 0.92 | 0.56 | 0.72 | 0.44 | 0.53 | 0.68 | 0.64 | 0.68 | 0.72 | 0.37 | 0.32 | 0.3 |
5 | 0.72 | 0.13 | 0.54 | 0.73 | 0.68 | 0.5 | 0.52 | 0.65 | 0.71 | 0.79 | 0.62 | 0.61 | 0.54 | 0.55 | 0.19 | 0.35 |
6 | 0.71 | 0.45 | 0.81 | 0.52 | 0.9 | 0.52 | 0.55 | 0.02 | 0.31 | 0.72 | 0.7 | 0.65 | 0.7 | 0.34 | 0.1 | 0.34 |
7 | 0.5 | 0.43 | 0.89 | 0.94 | 0.85 | 0.41 | 0.58 | 0.5 | 0.58 | 0.61 | 0.63 | 0.53 | 0.76 | 0.52 | 0.76 | 0.34 |
8 | 0.34 | 0.77 | 0.74 | 0.55 | 0.74 | 0.42 | 0.7 | 0.06 | 0.8 | 0.76 | 0.4 | 0.63 | 0.79 | 0.44 | 0.24 | 0.49 |
9 | 0.52 | 0.29 | 0.86 | 0.57 | 0.73 | 0.62 | 0.59 | 0.31 | 0.71 | 0.71 | 0.65 | 0.65 | 0.77 | 0.46 | 0.74 | 0.69 |
10 | 0.39 | 0.58 | 0.65 | 0.76 | 0.67 | 0.66 | 0.62 | 0.4 | 0.21 | 0.61 | 0.42 | 0.6 | 0.52 | 0.56 | 0.94 | 0.36 |
11 | 0.4 | 0.53 | 0.97 | 0.81 | 0.96 | 0.47 | 0.76 | 0.17 | 0.69 | 0.77 | 0.42 | 0.74 | 0.67 | 0.24 | 0.24 | 0.51 |
12 | 0.58 | 0.07 | 0.75 | 0.54 | 0.65 | 0.6 | 0.53 | 0.1 | 0.86 | 0.72 | 0.63 | 0.74 | 0.7 | 0.3 | 0.06 | 0.55 |
13 | 0.4 | 0.12 | 0.62 | 0.87 | 0.62 | 0.7 | 0.73 | 0.04 | 0.62 | 0.79 | 0.6 | 0.8 | 0.79 | 0.21 | 0.59 | 0.64 |
14 | 0.34 | 0.81 | 0.87 | 0.86 | 0.63 | 0.67 | 0.52 | 0.94 | 0.2 | 0.73 | 0.49 | 0.52 | 0.77 | 0.5 | 0.22 | 0.32 |
15 | 0.8 | 0.73 | 0.89 | 0.5 | 0.8 | 0.59 | 0.58 | 0.94 | 0.26 | 0.74 | 0.65 | 0.62 | 0.57 | 0.1 | 0.44 | 0.52 |
16 | 0.62 | 0.27 | 0.57 | 0.89 | 1.00 | 0.44 | 0.7 | 0.67 | 0.2 | 0.62 | 0.44 | 0.56 | 0.59 | 0.41 | 0.86 | 0.65 |
17 | 0.26 | 0.01 | 0.86 | 0.71 | 0.91 | 0.51 | 0.54 | 0.61 | 0.37 | 0.8 | 0.42 | 0.64 | 0.65 | 0.29 | 0.37 | 0.66 |
18 | 0.33 | 0.63 | 0.96 | 0.93 | 0.61 | 0.65 | 0.73 | 0.23 | 0.44 | 0.71 | 0.7 | 0.64 | 0.54 | 0.52 | 0.17 | 0.63 |
19 | 0.5 | 0.54 | 0.91 | 0.86 | 0.86 | 0.53 | 0.74 | 0.61 | 0.65 | 0.71 | 0.57 | 0.61 | 0.74 | 0.55 | 0.94 | 0.48 |
21 | 0.33 | 0.89 | 0.68 | 0.62 | 0.81 | 0.59 | 0.51 | 0.38 | 0.51 | 0.75 | 0.51 | 0.77 | 0.79 | 0.41 | 0.86 | 0.35 |
22 | 0.61 | 0.4 | 0.56 | 0.54 | 0.83 | 0.7 | 0.53 | 0.37 | 0.63 | 0.7 | 0.56 | 0.64 | 0.58 | 0.33 | 0.97 | 0.67 |
23 | 0.68 | 0.84 | 0.98 | 0.9 | 0.88 | 0.44 | 0.69 | 0.03 | 0.6 | 0.74 | 0.43 | 0.59 | 0.72 | 0.14 | 0.25 | 0.61 |
24 | 0.41 | 0.81 | 0.81 | 0.95 | 0.73 | 0.46 | 0.77 | 0.66 | 0.5 | 0.68 | 0.47 | 0.63 | 0.69 | 0.23 | 0.31 | 0.3 |
25 | 0.27 | 0.44 | 0.63 | 0.55 | 0.94 | 0.69 | 0.72 | 0.18 | 0.28 | 0.74 | 0.61 | 0.71 | 0.58 | 0.21 | 0.00 | 0.59 |
26 | 0.28 | 0.37 | 0.53 | 0.55 | 0.85 | 0.47 | 0.68 | 0.33 | 0.75 | 0.78 | 0.46 | 0.65 | 0.67 | 0.18 | 0.35 | 0.7 |
27 | 0.64 | 0.79 | 0.63 | 0.7 | 0.89 | 0.45 | 0.57 | 0.15 | 0.69 | 0.77 | 0.66 | 0.71 | 0.65 | 0.25 | 0.55 | 0.52 |
28 | 0.31 | 0.89 | 0.99 | 0.62 | 0.67 | 0.6 | 0.79 | 0.25 | 0.38 | 0.72 | 0.51 | 0.8 | 0.54 | 0.39 | 0.11 | 0.55 |
29 | 0.6 | 0.02 | 0.76 | 0.73 | 0.64 | 0.7 | 0.5 | 0.67 | 0.53 | 0.64 | 0.42 | 0.79 | 0.62 | 0.45 | 0.99 | 0.36 |
30 | 0.42 | 0.23 | 0.76 | 0.9 | 0.81 | 0.66 | 0.79 | 0.96 | 0.69 | 0.78 | 0.56 | 0.51 | 0.76 | 0.2 | 0.51 | 0.36 |
31 | 0.8 | 0.48 | 0.8 | 0.51 | 0.83 | 0.43 | 0.66 | 0.84 | 0.3 | 0.78 | 0.48 | 0.58 | 0.69 | 0.48 | 0.12 | 0.31 |
32 | 0.58 | 0.05 | 0.66 | 0.6 | 0.73 | 0.61 | 0.73 | 0.23 | 0.87 | 0.74 | 0.49 | 0.67 | 0.77 | 0.32 | 0.03 | 0.68 |
33 | 0.57 | 0.21 | 0.86 | 0.71 | 0.64 | 0.54 | 0.78 | 0.45 | 0.55 | 0.74 | 0.68 | 0.77 | 0.56 | 0.31 | 0.99 | 0.41 |
34 | 0.76 | 0.63 | 0.65 | 0.93 | 0.66 | 0.44 | 0.68 | 0.99 | 0.75 | 0.72 | 0.52 | 0.8 | 0.5 | 0.2 | 0.5 | 0.38 |
35 | 0.28 | 0.04 | 0.71 | 0.67 | 0.72 | 0.43 | 0.57 | 0.44 | 0.72 | 0.71 | 0.45 | 0.5 | 0.75 | 0.41 | 0.29 | 0.47 |
36 | 0.45 | 0.75 | 0.87 | 0.7 | 0.62 | 0.41 | 0.57 | 0.92 | 0.63 | 0.73 | 0.62 | 0.78 | 0.67 | 0.34 | 0.36 | 0.35 |
37 | 0.73 | 0.1 | 0.75 | 0.98 | 0.73 | 0.55 | 0.56 | 0.34 | 0.75 | 0.69 | 0.62 | 0.52 | 0.73 | 0.23 | 0.61 | 0.57 |
38 | 0.75 | 0.2 | 0.75 | 0.72 | 0.95 | 0.51 | 0.67 | 0.72 | 0.46 | 0.72 | 0.66 | 0.66 | 0.75 | 0.49 | 0.91 | 0.58 |
39 | 0.8 | 0.98 | 0.52 | 0.86 | 0.86 | 0.68 | 0.5 | 0.31 | 0.69 | 0.65 | 0.63 | 0.64 | 0.76 | 0.17 | 0.27 | 0.43 |
41 | 0.33 | 0.44 | 0.84 | 0.84 | 0.68 | 0.7 | 0.58 | 0.98 | 0.37 | 0.6 | 0.5 | 0.78 | 0.54 | 0.52 | 0.27 | 0.7 |
42 | 0.66 | 0.97 | 0.59 | 0.7 | 0.78 | 0.59 | 0.77 | 0.72 | 0.44 | 0.68 | 0.67 | 0.71 | 0.66 | 0.16 | 0.34 | 0.54 |
43 | 0.32 | 0.72 | 0.75 | 0.58 | 0.73 | 0.58 | 0.56 | 0.26 | 0.21 | 0.62 | 0.51 | 0.66 | 0.78 | 0.28 | 0.62 | 0.62 |
44 | 0.52 | 0.17 | 0.56 | 0.99 | 0.76 | 0.65 | 0.77 | 0.59 | 0.46 | 0.73 | 0.67 | 0.67 | 0.5 | 0.41 | 0.87 | 0.56 |
45 | 0.59 | 0.53 | 0.8 | 0.78 | 0.93 | 0.46 | 0.71 | 0.07 | 0.78 | 0.66 | 0.52 | 0.59 | 0.68 | 0.16 | 0.71 | 0.36 |
46 | 0.46 | 0.01 | 0.77 | 0.77 | 0.99 | 0.5 | 0.71 | 0.76 | 0.9 | 0.78 | 0.59 | 0.6 | 0.79 | 0.48 | 0.46 | 0.54 |
47 | 0.79 | 0.07 | 0.82 | 0.68 | 0.81 | 0.59 | 0.74 | 0.3 | 0.64 | 0.75 | 0.65 | 0.62 | 0.72 | 0.12 | 0.41 | 0.6 |
48 | 0.41 | 0.18 | 0.64 | 0.59 | 0.79 | 0.46 | 0.73 | 0.89 | 0.76 | 0.64 | 0.62 | 0.54 | 0.58 | 0.53 | 0.22 | 0.41 |
49 | 0.45 | 0.09 | 0.53 | 0.86 | 0.65 | 0.64 | 0.74 | 0.27 | 0.28 | 0.77 | 0.62 | 0.58 | 0.71 | 0.46 | 0.84 | 0.4 |
50 | 0.4 | 0.49 | 0.91 | 0.62 | 0.88 | 0.58 | 0.75 | 0.39 | 0.35 | 0.71 | 0.65 | 0.78 | 0.64 | 0.13 | 0.39 | 0.44 |
51 | 0.66 | 0.47 | 0.71 | 0.61 | 0.67 | 0.57 | 0.66 | 0.02 | 0.31 | 0.6 | 0.61 | 0.75 | 0.76 | 0.51 | 0.69 | 0.35 |
52 | 0.62 | 0.42 | 0.81 | 0.54 | 0.93 | 0.54 | 0.52 | 0.11 | 0.22 | 0.69 | 0.68 | 0.79 | 0.62 | 0.35 | 0.55 | 0.69 |
53 | 0.7 | 0.93 | 0.66 | 0.52 | 0.9 | 0.45 | 0.57 | 0.65 | 0.31 | 0.64 | 0.56 | 0.58 | 0.8 | 0.23 | 0.25 | 0.43 |
54 | 0.25 | 0.91 | 0.82 | 0.99 | 0.63 | 0.65 | 0.58 | 0.88 | 0.36 | 0.76 | 0.46 | 0.78 | 0.64 | 0.52 | 0.17 | 0.62 |
55 | 0.28 | 0.37 | 0.52 | 0.55 | 0.69 | 0.6 | 0.65 | 0.63 | 0.28 | 0.63 | 0.7 | 0.72 | 0.62 | 0.15 | 0.88 | 0.67 |
56 | 0.64 | 0.42 | 1.00 | 1.00 | 0.91 | 0.69 | 0.71 | 0.11 | 0.89 | 0.77 | 0.51 | 0.62 | 0.56 | 0.42 | 0.21 | 0.63 |
57 | 0.49 | 0.63 | 0.91 | 0.82 | 0.84 | 0.54 | 0.8 | 0.01 | 0.53 | 0.79 | 0.62 | 0.56 | 0.52 | 0.48 | 0.19 | 0.49 |
58 | 0.49 | 0.97 | 0.56 | 0.7 | 0.6 | 0.66 | 0.58 | 0.26 | 0.82 | 0.8 | 0.42 | 0.61 | 0.77 | 0.46 | 0.59 | 0.56 |
59 | 0.71 | 0.09 | 0.62 | 0.5 | 0.79 | 0.52 | 0.67 | 0.59 | 0.21 | 0.66 | 0.44 | 0.51 | 0.73 | 0.29 | 0.6 | 0.4 |
60 | 0.27 | 0.06 | 0.97 | 0.68 | 0.98 | 0.59 | 0.58 | 0.25 | 0.2 | 0.69 | 0.4 | 0.75 | 0.68 | 0.54 | 0.72 | 0.49 |
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