Team formation based on group technology: A hybrid grouping genetic algorithm approach

Computers and Operations Research

Volumn 38, Issue 2, 2011, Pages 484-495

  Agustín Blas, Luis E ^a   Salcedo Sanz, Sancho ^a   Ortiz García, Emilio G ^a   Portilla Figueras, Antonio ^a   Pérez Bellido, Ngel M ^a   Jiménez Fernández, Silvia ^a  

^a UNIVERSITY OF ALCALÁ   (Spain)

Author keywords

Group technology; Grouping genetic algorithms; Hybrid algorithms; Team formation

Indexed keywords

CELL FORMATION PROBLEM; CLASSICAL PROBLEMS; GROUPING GENETIC ALGORITHMS; HYBRID ALGORITHMS; NEW MODEL; REAL PROBLEMS; TEAM FORMATION;

CELLULAR MANUFACTURING; GENETIC ALGORITHMS; GROUP TECHNOLOGY; SIGNAL THEORY;

TECHNOLOGY;

EID: 77956410634     PISSN: 03050548     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.cor.2010.07.006     Document Type: Article

References (34)

1. A. Ballakur, and H.J. Steudel A within-cell utilization based heuristic for designing cellular manufacturing systems International Journal of Production Research 25 1987 639 655
2. M. Tavana, J.W. Smither, and R.V. Anderson D-side: a facility and workforce planning group multi-criteria decision support system for Johnson Space Center Computers & Operations Research 34 6 2007 1646 1673
3. M.P. Chandrasekharan, and R. Rajagopalan GROUPABILITY: an analysis of the properties of binary data matrices for group technology International Journal of Production Research 27 6 1989 1035 1052
4. C.S. Kumar, and M.P. Chandrasekharan Grouping efficacy: a quantitative criterion for goodness of block diagonal forms of binary matrices in group technology International Journal of Production Research 28 2 1990 233 243
5. H. Seifoddini, and M. Djassemi The threshold value of a quality index for formation of cellular manufacturing systems International Journal of Production Research 34 1996 3401 3416
6. B. Sarker, and S. Mondal Grouping efficiency measures in cellular manufacturing: a survey and critical review International Journal of Production Research 37 1999 285 314
7. B. Sarker Measures of group efficiency in cellular manufacturing systems European Journal of Operational Research 130 2001 588 611
8. S.M. Ng Worst-case analysis of an algorithm for cellular manufacturing European Journal of Operational Research 69 2 1993 384 398
9. K.B. Keeling, E.C. Brown, and T.L. James Grouping efficiency measures and their impact on factory measures for the machine-part cell formation problem: a simulation study Engineering Applications of Artificial Intelligence 20 2007 63 78
10. H. Wi, S. Oh, J. Mun, and M. Jung A team formation model based on knowledge and collaboration Expert Systems with Applications 36 5 2009 9121 9134
11. H. Wi, J. Mun, S. Oh, and M. Jung Modeling and analysis of project team formation factors in a project-oriented virtual organization (ProVO) Expert Systems with Applications 36 3 2009 5775 5783
12. Strnad D, Guid N. A fuzzy-genetic decision support system for project team formation. Applied Soft Computing, doi:10.1016/j.asoc.2009.08.032, in press.
13. T. Dereli, A. Baykasoglu, and G.S. Das Fuzzy quality-team formation for value added auditing: a case study Journal of Engineering and Technology Management 24 4 2007 366 394
14. T.L. Tseng, C.C. Huang, H.W. Chu, and R.R. Gung Novel approach to multi-functional project team formation International Journal of Project Management 22 2 2004 147 159
15. E.L. Fitzpatrick, and R.G. Askin Forming effective worker teams with multi-functional skill requirements Computers & Industrial Engineering 48 2005 593 608
16. Fan ZP, Chen Y, Mab J, Zhu Y. Decision support for proposal grouping: a hybrid approach using knowledge rules and genetic algorithms. Expert Systems with Applications 2009;36(2):100413.
17. T.L. James, E.C. Brown, and K.B. Keeling A hybrid grouping genetic algorithm for the cell formation problem Computers & Operations Research 34 2007 2059 2079
18. E.C. Brown, and R. Sumichrast CF-GGA: a grouping genetic algorithm for the cell formation problem International Journal of Production Research 36 2001 3651 3669
19. P. De Lit, E. Falkenauer, and A. Delchambre Grouping genetic algorithms: an efficient method to solve the cell formation problem Mathematics and Computers in Simulation 51 34 2000 257 271
20. K.H. Hindi, H. Yang, and K. Fleszar An evolutionary algorithm for resource-constrained project scheduling IEEE Transactions on Evolutionary Computation 6 5 2002 512 518
21. M.A. Bajestani, M. Rabbani, A.R. Rahimi-Vahed, and G.B. Khoshkhou A multi-objective scatter search for a dynamic cell formation problem Computers & Operations Research 36 3 2009 777 794
22. A. Ahi, M.B. Aryanezhad, B. Ashtiani, and A. Makui A novel approach to determine cell formation, intracellular machine layout and cell layout in the CMS problem based on TOPSIS method Computers & Operations Research 36 5 2009 1478 1496
23. S. Wang, and S.J. Lin The effects of group composition of self-efficacy and collective efficacy on computer-supported collaborative learning Computers in Human Behaviour 23 2007 2256 2268
24. D.Y. Wang, S.J. Lin, and C.T. Sun DIANA: a computer-supported heterogeneous grouping system for teachers to conduct successful small learning groups Computers in Human Behaviour 23 2007 1997 2010
25. J. Burbridge Group technology in the engineering industry 1979 Wiley New York
26. E. Falkenauer The grouping genetic algorithmwidening the scope of the GAs Proceedings of the Belgian journal of operations research, statistics and computer science vol. 33 1992 79 102
27. E. Falkenauer Genetic algorithms for grouping problems 1998 Wiley New York
28. E.C. Brown, and M. Vroblefski A grouping genetic algorithm for the microcell sectorization problem Engineering Applications of Artificial Intelligence 17 6 2004 589 598
29. T. James, M. Vroblefski, and Q. Nottingham A hybrid grouping genetic algorithm for the registration area planning problem Computer Communications 30 10 2007 2180 2190 (Pubitemid 47094961)
30. L.E. Agustn-Blas, S. Salcedo-Sanz, E.G. Ortiz-Garca, A. Portilla-Figueras, and A.M. Prez-Bellido A hybrid grouping genetic algorithm for assigning students to preferred laboratory groups Expert Systems with Applications 36 2009 7234 7241
31. C. Hung, R.T. Sumichrast, and E.C. Brown CPGEA: a grouping genetic algorithm for material cutting plan generation Computers & Industrial Engineering 44 4 2003 651 672
32. D. Whitley, S. Rana, and R.B. Heckendorn The island model genetic algorithm, population size and convergence: on separability Journal of Computing and Information Technology 7 1999 33 47
33. T. Meyer, A.T. Ernst, and M. Krishnamoorthy A 2-phase algorithm for solving the single allocation p-hub center problem Computers & Operations Research 36 2009 3143 3151
34. R. Santiago-Mozos, S. Salcedo-Sanz, M. DePrado-Cumplido, and C. Bousoo-Calzn A two-phase heuristic evolutionary algorithm for personalizing course timetables: a case study in a Spanish University Computers & Operations Research 32 7 2005 1761 1776