A Novel Pareto-VIKOR Index for Ranking Scientists’ Publication Impacts: A Case Study on Evolutionary Computation Researchers

Scientists’ publication impacts ranking is an important topic in scientometrics which is performed based on various proposed criteria. One of the well-known indicators is h-index which evaluates researchers achievements based on number of citations. The h-index has utilized in many research data sources because of its appropriate properties, but similar to other assessment indicators, it has own disadvantages. hindex cannot give a fair comparison between junior and senior researches. There are two reasons for this unfair comparison: (1) h-index depends on the research period of scholars and (2) the number of received citations can be increased by time, even if researcher doesn’t publish new papers, the h-index increases. Consequently, in addition to h-index, the number of the years of academic research (called the research period) is preferable to be considered as an independent indicator, which makes us able to have a more fair evaluation. So these two objectives, maximizing h-index and minimizing research period, can be considered as a multi-criteria comparison task to assess researchers. In this paper, we propose a strategy based on Pareto dominance ranking which uses dominance concept to obtain an order for researchers. In order to complete ranking between scientists in the same rank, a multi-criteria decision making measure called VIKOR is utilized. Therefore, a total ranking measure (P-V index) is obtained using Perto front concept and VIKOR measure. The proposed method is applied on 235 researchers who are conducting research on Evolutionary Computation (EC) topic. The h-index value and the research period of scholars are collected via Google Scholar service. P-V index obtains 26 Pareto ranks for all researchers and places six EC scientists on the first Pareto front.

[1]  Loet Leydesdorff,et al.  A review of theory and practice in scientometrics , 2015, Eur. J. Oper. Res..

[2]  Carlos A. Coello Coello,et al.  Evolutionary multi-objective optimization: a historical view of the field , 2006, IEEE Comput. Intell. Mag..

[3]  Gwo-Hshiung Tzeng,et al.  Extended VIKOR method in comparison with outranking methods , 2007, Eur. J. Oper. Res..

[4]  R. M. Hayes Citation Statistics as a Measure of Faculty Research Productivity , 1983 .

[5]  Massimo Franceschet,et al.  A comparison of bibliometric indicators for computer science scholars and journals on Web of Science and Google Scholar , 2010, Scientometrics.

[6]  Anthony F. J. van Raan Comparison of the Hirsch-index with standard bibliometric indicators and with peer judgment for 147 chemistry research groups , 2013, Scientometrics.

[7]  B. Frey,et al.  Quantitative and Qualitative Rankings of Scholars , 2011 .

[8]  Evangelos Triantaphyllou,et al.  Multi-Criteria Decision Making Methods , 2000 .

[9]  L. Bornmann,et al.  The state of h index research , 2009, EMBO reports.

[10]  Kalyanmoy Deb,et al.  A fast and elitist multiobjective genetic algorithm: NSGA-II , 2002, IEEE Trans. Evol. Comput..

[11]  J. E. Hirsch,et al.  An index to quantify an individual's scientific research output , 2005, Proc. Natl. Acad. Sci. USA.

[12]  M. Sayadi,et al.  Extension of VIKOR method for decision making problem with interval numbers , 2009 .

[13]  Rodrygo L. T. Santos,et al.  Aggregating productivity indices for ranking researchers across multiple areas , 2013, JCDL '13.

[14]  Sergey N. Dorogovtsev,et al.  Ranking scientists , 2015, Nature Physics.

[15]  Lutz Bornmann,et al.  Alternative metrics in scientometrics: a meta-analysis of research into three altmetrics , 2015, Scientometrics.

[16]  Asim F Choudhri,et al.  Part II: Should the h-index be modified? An analysis of the m-quotient, contemporary h-index, authorship value, and impact factor. , 2013, World neurosurgery.

[17]  Jasbir S. Arora,et al.  Survey of multi-objective optimization methods for engineering , 2004 .