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Journal articles on the topic 'Multiple criteria analysis'

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Published: 4 June 2021
Last updated: 31 May 2022

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1

Nuthall, P. L. "MULTIPLE CRITERIA ANALYSIS." Agricultural Economics 5, no. 2 (June 1991): 174–78. http://dx.doi.org/10.1111/j.1574-0862.1991.tb00147.x.

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2

Flores, Benito E., and D. Clay Whybark. "Multiple Criteria ABC Analysis." International Journal of Operations & Production Management 6, no. 3 (March 1986): 38–46. http://dx.doi.org/10.1108/eb054765.

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3

Antoine, Jacques, Günther Fischer, and Marek Makowski. "Multiple criteria land use analysis." Applied Mathematics and Computation 83, no. 2-3 (May 1997): 195–215. http://dx.doi.org/10.1016/s0096-3003(96)00190-7.

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4

Zavadskas, E. K., A. Kaklauskas, N. Lepkova, and J. Zalatorius. "FACILITIES MANAGEMENT MULTIPLE CRITERIA ANALYSIS." Statyba 7, no. 6 (January 2001): 481–89. http://dx.doi.org/10.1080/13921525.2001.10531776.

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5

Flores, Benito E., and D. Clay Whybark. "Implementing multiple criteria ABC analysis." Engineering Costs and Production Economics 15 (May 1989): 191–95. http://dx.doi.org/10.1016/0167-188x(89)90124-9.

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6

Flores, Benito E., and D. Clay Whybark. "Implementing multiple criteria ABC analysis." Journal of Operations Management 7, no. 1-2 (October 1987): 79–85. http://dx.doi.org/10.1016/0272-6963(87)90008-8.

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7

Nijkamp, Peter. "MULTIPLE CRITERIA ANALYSIS AND INTEGRATED IMPACT ANALYSIS." Impact Assessment 4, no. 3-4 (March 1986): 226–61. http://dx.doi.org/10.1080/07349165.1986.9725786.

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8

Nijkamp, Peter, Hans Schaffers, and Jaap Spronk. "Multiple futures and multiple discount rates in multiple criteria analysis." Project Appraisal 4, no. 1 (March 1989): 2–8. http://dx.doi.org/10.1080/02688867.1989.9726699.

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9

Kaftanowicz, Michał, and Michał Krzemiński. "Multiple-criteria Analysis of Plasterboard Systems." Procedia Engineering 111 (2015): 364–70. http://dx.doi.org/10.1016/j.proeng.2015.07.102.

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10

Greene, Randal, Rodolphe Devillers, Joan E. Luther, and Brian G. Eddy. "GIS-Based Multiple-Criteria Decision Analysis." Geography Compass 5, no. 6 (June 2011): 412–32. http://dx.doi.org/10.1111/j.1749-8198.2011.00431.x.

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11

Haimes, Yacov Y. "Multiple-criteria decisionmaking: A retrospective analysis." IEEE Transactions on Systems, Man, and Cybernetics SMC-15, no. 3 (May 1985): 313–15. http://dx.doi.org/10.1109/tsmc.1985.6313365.

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12

Kostreva, Michael M., Włodzimierz Ogryczak, and Adam Wierzbicki. "Equitable aggregations and multiple criteria analysis." European Journal of Operational Research 158, no. 2 (October 2004): 362–77. http://dx.doi.org/10.1016/j.ejor.2003.06.010.

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13

McGregor, Murray. "Multiple criteria analysis for agricultural decisions." Agricultural Systems 33, no. 3 (January 1990): 291–92. http://dx.doi.org/10.1016/0308-521x(90)90056-v.

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14

Chen, Ye, D. Marc Kilgour, and Keith W. Hipel. "Screening in multiple criteria decision analysis." Decision Support Systems 45, no. 2 (May 2008): 278–90. http://dx.doi.org/10.1016/j.dss.2007.12.017.

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15

Brožová, H. "The analytic hierarchy process for the decision tree with multiple criteria." Agricultural Economics (Zemědělská ekonomika) 50, No. 2 (February 24, 2012): 77–82. http://dx.doi.org/10.17221/5170-agricecon.

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For choosing the best decision in daily agricultural practice, it is very important to formalize the decision process using systems analysis and mathematical methods. Theory of the decision-making under uncertainty or under risk supposes one criterion. In practice, the best solution is chosen under more decision criteria. Decision problem with <i>m</i> alternatives, <i>n</i> states of nature and k criteria has to be solved in this case. Application of the Analytic Hierarchy Process (AHP) for solution of this problem is described in this paper.
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16

Delias, Pavlos, Georgia Kyriakaki, Evangelos Grigoroudis, and Nikolaos Matsatsinis. "Innovation Management Software Exploiting Multiple Criteria Analysis." International Journal of Decision Support System Technology 4, no. 1 (January 2012): 30–42. http://dx.doi.org/10.4018/jdsst.2012010103.

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Innovation is a critical factor in building an organization’s culture of growth. Provided that it is properly blended with organizational development initiatives and aligned with the organization’s strategy, it supplies a compelling advantage for the growth process. Neglecting to encompass innovation in an organization’s culture could lead to shrinkage and even extinction, in the case of an intensively competitive market. Executive staff must consider innovative technologies and be aware of all growth opportunities. However, this staff is stressed under information overload. A need exists to reduce the information load and filter available technologies according to the specific needs of the organization. In this paper, the authors propose a recommendation approach to match the needs of an organization against existing technologies (innovative products or services). The organization expresses its customized needs by declaring its preferences over a small reference set of indicative technologies. Each technology is characterized by multiple attributes, in a way that the organization ultimately expresses the trade-offs between the attributes’ significance weights. This information is used to create the organization’s profile. The profile guides a recommendation process, according to which available technologies are evaluated against the profile and proposed to the organization in a descending order.
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17

Maliene, Vida. "Specialised property valuation: Multiple criteria decision analysis." Journal of Retail & Leisure Property 9, no. 5 (May 2011): 443–50. http://dx.doi.org/10.1057/rlp.2011.7.

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18

Barin, Alexandre, Luciane N. Canha, Alzenira R. Abaide, Karine F. Magnago, Breno Wottrich, and Ricardo Q. Machado. "Multiple Criteria Analysis for Energy Storage Selection." Energy and Power Engineering 03, no. 04 (2011): 557–64. http://dx.doi.org/10.4236/epe.2011.34069.

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19

Malinauskas, P., and T. Petrašsenko. "MULTIPLE CRITERIA ANALYSIS OF DWELLING FACILITIES MAINTENANCE." Statyba 7, no. 2 (January 2001): 138–47. http://dx.doi.org/10.1080/13921525.2001.10531715.

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20

Reiff, Marian, Kvetoslava Surmanová, Adam P. Balcerzak, and Michał Bernard Pietrzak. "Multiple Criteria Analysis of European Union Agriculture." Journal of International Studies 9, no. 3 (November 2016): 62–74. http://dx.doi.org/10.14254/2071-8330.2016/9-3/5.

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21

Meyer, Patrick. "Progressive methods in multiple criteria decision analysis." 4OR 7, no. 2 (June 25, 2008): 191–94. http://dx.doi.org/10.1007/s10288-008-0069-5.

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22

Kaklauskas, A., E. K. Zavadskas, A. Radzeviciene, I. Ubarte, A. Podviezko, V. Podvezko, A. Kuzminske, A. Banaitis, A. Binkyte, and V. Bucinskas. "Quality of city life multiple criteria analysis." Cities 72 (February 2018): 82–93. http://dx.doi.org/10.1016/j.cities.2017.08.002.

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23

Aydin Keskin, Gulsen, and Coskun Ozkan. "Multiple Criteria ABC Analysis with FCM Clustering." Journal of Industrial Engineering 2013 (December 18, 2013): 1–7. http://dx.doi.org/10.1155/2013/827274.

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The number of stock keeping units (SKUs) possessed by organizations can easily reach quite a few. An inventory management policy for each individual SKU is not economical to design. ABC analysis is one of the conventionally used approaches to classify SKUs. In the classical method, the SKUs are ranked with respect to the descending order of the annual dollar usage, which is the product of unit price and annual demand. The few of the SKUs that have the highest annual dollar usage are in group A and should be taken into account mostly; the SKUs with the least annual dollar usage are in group C and should be taken into account least; the remaining SKUs are in group B. In this study, we proposed fuzzy c-means (FCM) clustering to a multicriteria ABC analysis problem to help managers to make better decision under fuzzy circumstancse. The obtained results show that the FCM is a quite simple and an easily adaptable method to inventory management.
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24

Balcerzak, Adam P. "Technological Potential of European Economy. Proposition of Measurement with Application of Multiple Criteria Decision Analysis." MONTENEGRIN JOURNAL OF ECONOMICS 12, no. 3 (October 20, 2016): 7–17. http://dx.doi.org/10.14254/1800-5845.2016/12-3/1.

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25

Singh, Chanchal. "A class of multiple-criteria fractional programming problems." Journal of Mathematical Analysis and Applications 115, no. 1 (April 1986): 202–13. http://dx.doi.org/10.1016/0022-247x(86)90034-x.

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26

Hu, Pei-Chu, and Da-Wei Meng. "Normality criteria of meromorphic functions with multiple zeros." Journal of Mathematical Analysis and Applications 357, no. 2 (September 2009): 323–29. http://dx.doi.org/10.1016/j.jmaa.2009.04.016.

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27

Thokala, Praveen, and Alejandra Duenas. "Multiple Criteria Decision Analysis for Health Technology Assessment." Value in Health 15, no. 8 (December 2012): 1172–81. http://dx.doi.org/10.1016/j.jval.2012.06.015.

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28

Hapke, Maciej, Andrzej Jaszkiewicz, and Roman Słowiński. "Interactive analysis of multiple-criteria project scheduling problems." European Journal of Operational Research 107, no. 2 (June 1998): 315–24. http://dx.doi.org/10.1016/s0377-2217(97)00336-6.

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29

Li, Xiao-Bai, and Gary R. Reeves. "A multiple criteria approach to data envelopment analysis." European Journal of Operational Research 115, no. 3 (June 1999): 507–17. http://dx.doi.org/10.1016/s0377-2217(98)00130-1.

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30

Bradley, Ralph A., and Frances P. Stewart. "Intrablock Analysis of Designs with Multiple Blocking Criteria." Journal of the American Statistical Association 86, no. 415 (September 1991): 792–97. http://dx.doi.org/10.1080/01621459.1991.10475111.

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31

Peldschus, Friedel. "MULTIPLE-CRITERIA ANALYSIS IN THE CONSTRUCTION OF MOTORWAYS." Technological and Economic Development of Economy 11, no. 1 (March 31, 2005): 32–35. http://dx.doi.org/10.3846/13928619.2005.9637680.

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Several construction variants are discussed for the extension of the motorway network in Thuringia (Germany). The best variant is determined according to several criteria: construction period, costs, durability, environmental protection and economic viability. After the characterisation of the considered construction solutions a numerical comparison is made using the software LEVI 3.0. Thereby the optimal variant is chosen taking into account the mentionned criteria and the solution is explained.
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32

Kvederytė, N., E. K. Zavadskas, and A. Kaklauskas. "MULTIPLE CRITERIA ANALYSIS OF A DWELLING LIFE CYCLE." Statyba 6, no. 3 (January 2000): 179–92. http://dx.doi.org/10.1080/13921525.2000.10531585.

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33

Janssen, Ron, and Peter Nijkamp. "A Typological Approach to Multiple Criteria Conflict Analysis." Conflict Management and Peace Science 9, no. 2 (February 1986): 45–53. http://dx.doi.org/10.1177/073889428600900204.

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34

Chang, Chia-Ling. "A modified VIKOR method for multiple criteria analysis." Environmental Monitoring and Assessment 168, no. 1-4 (August 12, 2009): 339–44. http://dx.doi.org/10.1007/s10661-009-1117-0.

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35

Carneiro, João, Luís Conceição, Diogo Martinho, Goreti Marreiros, and Paulo Novais. "Including cognitive aspects in multiple criteria decision analysis." Annals of Operations Research 265, no. 2 (December 21, 2016): 269–91. http://dx.doi.org/10.1007/s10479-016-2391-1.

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36

Hatami-Marbini, Adel, and Mehdi Toloo. "An extended multiple criteria data envelopment analysis model." Expert Systems with Applications 73 (May 2017): 201–19. http://dx.doi.org/10.1016/j.eswa.2016.12.030.

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37

Mullen, Jeffrey D. "Multiple criteria analysis for agricultural decisions, second edition." Agricultural Systems 82, no. 1 (October 2004): 96–97. http://dx.doi.org/10.1016/j.agsy.2004.02.006.

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38

Ng, Wan Lung. "A simple classifier for multiple criteria ABC analysis." European Journal of Operational Research 177, no. 1 (February 2007): 344–53. http://dx.doi.org/10.1016/j.ejor.2005.11.018.

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39

Doyle, J., and R. Green. "Data envelopment analysis and multiple criteria decision making." Omega 21, no. 6 (November 1993): 713–15. http://dx.doi.org/10.1016/0305-0483(93)90013-b.

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40

Herath, Gamini. "Multiple Criteria Analysis for Agricultural Decisions, Second Edition." Ecological Economics 51, no. 1-2 (November 2004): 159–60. http://dx.doi.org/10.1016/j.ecolecon.2004.05.001.

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41

Prato, Tony, and Gamini Herath. "Multiple-criteria decision analysis for integrated catchment management." Ecological Economics 63, no. 2-3 (August 2007): 627–32. http://dx.doi.org/10.1016/j.ecolecon.2007.01.003.

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42

Shi, Y., P. L. Yu, and D. Z. Zhang. "Eliminating Permanently Dominated Opportunities in Multiple-Criteria and Multiple-Constraint Level Linear Programming." Journal of Mathematical Analysis and Applications 183, no. 3 (May 1994): 685–705. http://dx.doi.org/10.1006/jmaa.1994.1175.

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43

Fordoni, Sarvar, and Rashid Melit. "Multiple Selections of Kashmir Tunnel Risk by Fuzzy Multiple-Criteria Decision Analysis." Journal of Bioinformatics and Intelligent Control 4, no. 1 (March 1, 2015): 67–74. http://dx.doi.org/10.1166/jbic.2015.1115.

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44

Ghaffariyan, M. R., and M. Brown. "Selecting the efficient harvesting method using multiple-criteria analysis: A case study in south-west Western Australia." Journal of Forest Science 59, No. 12 (December 20, 2013): 479–86. http://dx.doi.org/10.17221/45/2013-jfs.

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Different factors can impact on the timber harvesting methods including stand characteristics, ground conditions, extraction distance, climate, silvicultural treatments and social interests. The multiple-criteria analysis is an effective methodology for helping foresters decide what system to apply depending on their operations specifications. Four harvesting methods were compared in Western Australian Eucalypt plantations including cut-to-length (CTL), in-field chipping using a delimbing and debarking flail integrated with the chipper (IFC-DDC), in-field chipping using a chipper with a separate flail machine for delimbing and debarking (IFC-F/C) and whole tree to roadside (WTR). The decision criterions consisted of total operating cost (from stand to mill gate), yield per ha, harvesting residues, fuel consumption and bark content of the chips. The Promethee method was used to evaluate the alternatives using Decision Lab software. Based on the results, the IFC-DCC was the best harvest method while WTR method was the worst harvesting alternative in the case study area. IFC-DCC method resulted in the lowest operating cost and the highest recovered yield per ha compared to the other harvesting methods.
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45

Francik, Sławomir, Norbert Pedryc, Adrian Knapczyk, Artur Wójcik, Renata Francik, and Bogusława Łapczyńska-Kordon. "Bibliometric analysis of multiple criteria decision making in agriculture." Technical Sciences 1, no. 20 (December 15, 2016): 17–30. http://dx.doi.org/10.31648/ts.2906.

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Development trends (Research Trends) in scientific research on the methods of Multiple Criteria Decision Making (MCDM) and Multiple Criteria Decision Analysis (MCDA) in agriculture are analyzed. Established bibliometric techniques are applied. MCDA/MCDM methods are being very intensively developed in recent years, as evidenced by the number of scientific papers published annually in renowned scientific journals indexed in the Web of Science (WoS) database. In the years 1979-2015 a total of 1,355 scientific articles were collected in the database. The number of articles published annually increased rapidly after 2005. Besides, the annual number of citations of the publications is increasing. Research on MCDA/MCDM is conducted in many research areas. In the years 1984-2015 the Web of Science database accumulated 27 scientific publications on MCDA/MCDM in agriculture area. Therefore, it can be concluded that the MCDA/MCDM issues are currently not sufficiently analyzed in relation to agriculture. In the future this subject will probably be further developed, an increasing number of scientists will conduct research on the MCDA/MCDM and the annual number of articles published in the field will increase.
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46

Rogalska, Elżbieta. "Multiple-criteria analysis of regional entrepreneurship conditions in Poland." Equilibrium 13, no. 4 (December 31, 2018): 707–23. http://dx.doi.org/10.24136/eq.2018.034.

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Research background: Building effective conditions for doing business and sup-porting entrepreneurs is currently considered as a basic growth determinant. It is a policy objective not only at the national level, but also an important factor influencing the competitive potential of regions and local communities. It is especially important in the case of Central European countries and regions that face the problem of closing development gap. Therefore, comparative research with regard to entrepreneurship conditions, especially at spatially lower aggregation level, can provide important background for proposing policy guidelines. Purpose of the article: The main objective of the article is to analyse changes in disparities in regard to entrepreneurship conditions in Poland at NUTS 3 level in the years 2010 and 2015. Methods: The entrepreneurship conditions are analysed based on 5 criteria. As a result, they are considered as a multiple-criteria phenomenon. Therefore, in the article the dynamic analysis was implemented, where taxonomic measure of development was assessed with TOPSIS method based on median vector Weber. The obtained taxonomic measure allowed to rank the NUTS 3 regions starting with the ones characterised with the best conditions for entrepreneurs to the ones with the worst conditions, to group then into relatively homogenous subsets, and finally to verify the changes in the disparities between the regions in the analysed period. Findings & Value added: The research confirms that in spite of visible improvements significant disparities at the regional level in regard to entrepreneurial conditions should be considered as an actual and important problem for regional policy in Poland. This factor can negatively affect the possibilities of reaching spatially sustainable growth objectives. From the long-term perspective, the disparities can still negatively affects social and political growth environment in Poland.
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47

K.R, Prema, Prabhalakshmi K.K, and Merin Jose. "MULTIPLE MYELOMA- ANALYSIS OF DIAGNOSTIC CRITERIA AND PROGNOSTIC FACTORS." Journal of Evidence Based Medicine and Healthcare 5, no. 50 (December 8, 2018): 3440–45. http://dx.doi.org/10.18410/jebmh/2018/700.

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48

Thokala, P. "PRM42 Multiple Criteria Decision Analysis for Health Technology Assessment." Value in Health 15, no. 7 (November 2012): A652. http://dx.doi.org/10.1016/j.jval.2012.08.292.

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49

Kaklauskas, A. "Neuro Multiple Criteria Analysis System for University-Industry Partnerships." Procedia Engineering 212 (2018): 93–100. http://dx.doi.org/10.1016/j.proeng.2018.01.013.

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50

Thokala, P. "Operationalising Multiple Criteria Decision Analysis For Health Technology Assessment." Value in Health 16, no. 3 (May 2013): A270. http://dx.doi.org/10.1016/j.jval.2013.03.1392.

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