A Method for the Team Selection Problem Between Two Decision-Makers Using the Ant Colony Optimization

The team selection issue is important in the management of human resources, in which the purpose is to conduct a personnel selection process to form teams according to certain preferences. This selection problem is usually solved by ranking the candidates based on the preferences of decision-makers and allowing the decision-makers to select a candidate on its turn. While this solution method is simple and might seem fair it usually results in an unfair allocation of candidates to the different teams, i.e. the quality of the teams might be quite different according to the rankings articulated by the decision-makers. In this paper we propose a new approach to the team selection problem in which two employers should form their teams selecting personnel from a set of candidates that is common to both; each decision-maker has a personal ranking of those candidates. The objective it to make teams of high quality according to the valuation of each of the decision-makers; this results in a method for the team selection problem which not only result in high quality teams, but also focuses on a fair composition of the teams. Our approach is based on the Ant Colony Optimization metaheuristic, and allows to solve large instances of the problem as shown in the experimental section of this paper.

[1]  Bertrand Mareschal,et al.  Prométhée: a new family of outranking methods in multicriteria analysis , 1984 .

[2]  Thomas Stützle,et al.  MAX-MIN Ant System , 2000, Future Gener. Comput. Syst..

[3]  Toshiharu Sugawara,et al.  Role and member selection in team formation using resource estimation for large-scale multi-agent systems , 2014, Neurocomputing.

[4]  Sergey Shvydun,et al.  An Effective Personnel Selection Model , 2014, ITQM.

[5]  Majid Mojahed,et al.  Personnel selection using ELECTRE , 2010 .

[6]  Metin Dagdeviren,et al.  A hybrid multi-criteria decision-making model for personnel selection in manufacturing systems , 2010, J. Intell. Manuf..

[7]  R. Amit,et al.  Human resources management processes: a value-creating source of competitive advantage , 1999 .

[8]  Marco Dorigo,et al.  Ant system: optimization by a colony of cooperating agents , 1996, IEEE Trans. Syst. Man Cybern. Part B.

[9]  Jian Wang,et al.  A win-win team formation problem based on the negotiation , 2015, Eng. Appl. Artif. Intell..

[10]  Carol T. Kulik,et al.  The Multiple-Category Problem: Category Activation and Inhibition in the Hiring Process , 2007 .

[11]  Asli Özdemir A two-phase multi criteria dynamic programing approach for personnel selection process , 2017 .

[12]  Marco Dorigo,et al.  Ant algorithms and stigmergy , 2000, Future Gener. Comput. Syst..

[13]  Luca Maria Gambardella,et al.  Ant Algorithms for Discrete Optimization , 1999, Artificial Life.

[14]  Kalyanmoy Deb,et al.  Multi-objective optimization and decision making approaches to cricket team selection , 2013, Appl. Soft Comput..

[15]  Mark A. Huselid The Impact of Human Resource Management Practices on Turnover, Productivity, and Corporate Financial Performance , 1995 .

[16]  Diyar Akay,et al.  Personnel selection based on intuitionistic fuzzy sets , 2011 .

[17]  Marco Dorigo,et al.  Ant colony optimization , 2006, IEEE Computational Intelligence Magazine.

[18]  Alvydas Balezentis,et al.  Personnel selection based on computing with words and fuzzy MULTIMOORA , 2012, Expert Syst. Appl..

[19]  San-yang Liu,et al.  A GRA-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection , 2011, Expert Syst. Appl..

[20]  Enric Crespo,et al.  Personnel selection based on fuzzy methods , 2011 .

[21]  Saadettin Erhan Kesen,et al.  A fuzzy AHP approach to personnel selection problem , 2009, Appl. Soft Comput..

[22]  Vicente Liern,et al.  Soft computing-based aggregation methods for human resource management , 2008, Eur. J. Oper. Res..

[23]  Dimitris Askounis,et al.  A new TOPSIS-based multi-criteria approach to personnel selection , 2010, Expert Syst. Appl..

[24]  Young-Jou Lai,et al.  IMOST: Interactive Multiple Objective System Technique , 1995 .

[25]  Dejiang Wang,et al.  Extension of TOPSIS Method for R&D Personnel Selection Problem with Interval Grey Number , 2009, 2009 International Conference on Management and Service Science.

[26]  Adem Göleç,et al.  A fuzzy model for competency-based employee evaluation and selection , 2007, Comput. Ind. Eng..

[27]  Madjid Tavana,et al.  A fuzzy inference system with application to player selection and team formation in multi-player sports , 2013 .

[28]  Martina Huemann,et al.  Human resource management in the project-oriented company: A review , 2007 .

[29]  Annika Kangas,et al.  Outranking methods as tools in strategic natural resources planning , 2001 .

[30]  Dimitris Askounis,et al.  An extension of fuzzy TOPSIS for personnel selection , 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

[31]  Vicente Liern,et al.  Soft Computing Methods for Personnel Selection Based on the Valuation of Competences , 2014, Int. J. Intell. Syst..

[32]  Sen-Kuei Liao,et al.  Selecting Public Relations Personnel of Hospitals by Analytic Network Process , 2009, Journal of hospital marketing & public relations.

[33]  Serhat Burmaoglu,et al.  A fuzzy hybrid MCDM approach for professional selection , 2012, Expert Syst. Appl..

[34]  Edmundas Kazimieras Zavadskas,et al.  Multi-criteria assessment and ranking system of sport team formation based on objective-measured values of criteria set , 2014, Expert Syst. Appl..

[35]  E. Ertugrul Karsak,et al.  A fuzzy MCDM approach for personnel selection , 2010, Expert Syst. Appl..

[36]  Chen-Fu Chien,et al.  Data mining to improve personnel selection and enhance human capital: A case study in high-technology industry , 2008, Expert Syst. Appl..

[37]  Metin Da ˘ gdeviren A hybrid multi-criteria decision-making model for personnel selection in manufacturing systems , 2010 .

[38]  Peter Vrancx,et al.  Multi-type Ant Colony: The Edge Disjoint Paths Problem , 2004, ANTS Workshop.

[39]  Chen-Tung Chen,et al.  Applying multiple linguistic PROMETHEE method for personnel evaluation and selection , 2009, 2009 IEEE International Conference on Industrial Engineering and Engineering Management.

[40]  Damjan Strnad,et al.  A fuzzy-genetic decision support system for project team formation , 2010, Appl. Soft Comput..

[41]  Sancho Salcedo-Sanz,et al.  Team formation based on group technology: a hybrid grouping genetic algorithm approach , 2011, IEEE Engineering Management Review.