Geodesic
Application of self-gonfiguring genetic algorithm for human resource management
Žurnal Sibirskogo federalʹnogo universiteta. Matematika i fizika, Tome 8 (2015) no. 1, pp. 94-103.

Voir la notice de l'article provenant de la source Math-Net.Ru

This paper describes the problem of human resource management which can appear in many organizations during restructuration periods. The problem is simulated by a dynamic model, similar to a supply chain model with several ranks. The problem of finding the optimal combination of transition coefficients, including the fluctuation coefficients, is transformed into an optimization problem. To solve this problem, a self-configuring genetic algorithm is applied with several constraint handling methods. Additional constraints are defined in order to avoid undesirable oscillations in the system. The results show that this problem can be efficiently solved by the presented methods.
Keywords: human resources management, genetic algorithm, constrained optimization, self-configuration.
Mots-clés : simulation 
@article{JSFU_2015_8_1_a11,
     author = {Andrej \v{S}kraba and Davorin Kofja\v{c} and Anja \v{Z}nidar\v{s}i\v{c} and Matja\v{z} Maleti\v{c} and \v{C}rtomir Rozman and Eugene S. Semenkin and Maria E. Semenkina and Vladimir V. Stanovov},
     title = {Application of self-gonfiguring genetic algorithm for human resource management},
     journal = {\v{Z}urnal Sibirskogo federalʹnogo universiteta. Matematika i fizika},
     pages = {94--103},
     publisher = {mathdoc},
     volume = {8},
     number = {1},
     year = {2015},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/JSFU_2015_8_1_a11/}
}
TY  - JOUR
AU  - Andrej Škraba
AU  - Davorin Kofjač
AU  - Anja Žnidaršič
AU  - Matjaž Maletič
AU  - Črtomir Rozman
AU  - Eugene S. Semenkin
AU  - Maria E. Semenkina
AU  - Vladimir V. Stanovov
TI  - Application of self-gonfiguring genetic algorithm for human resource management
JO  - Žurnal Sibirskogo federalʹnogo universiteta. Matematika i fizika
PY  - 2015
SP  - 94
EP  - 103
VL  - 8
IS  - 1
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/JSFU_2015_8_1_a11/
LA  - en
ID  - JSFU_2015_8_1_a11
ER  - 
%0 Journal Article
%A Andrej Škraba
%A Davorin Kofjač
%A Anja Žnidaršič
%A Matjaž Maletič
%A Črtomir Rozman
%A Eugene S. Semenkin
%A Maria E. Semenkina
%A Vladimir V. Stanovov
%T Application of self-gonfiguring genetic algorithm for human resource management
%J Žurnal Sibirskogo federalʹnogo universiteta. Matematika i fizika
%D 2015
%P 94-103
%V 8
%N 1
%I mathdoc
%U http://geodesic.mathdoc.fr/item/JSFU_2015_8_1_a11/
%G en
%F JSFU_2015_8_1_a11
Andrej Škraba; Davorin Kofjač; Anja Žnidaršič; Matjaž Maletič; Črtomir Rozman; Eugene S. Semenkin; Maria E. Semenkina; Vladimir V. Stanovov. Application of self-gonfiguring genetic algorithm for human resource management. Žurnal Sibirskogo federalʹnogo universiteta. Matematika i fizika, Tome 8 (2015) no. 1, pp. 94-103. http://geodesic.mathdoc.fr/item/JSFU_2015_8_1_a11/

[1] A. Škraba, M. Kljajić, P. Papler, D. Kofjač, M. Obed, “Determination of recruitment and transition strategies”, Kybernetes, 40:9/10 (2011), 1503–1522

[2] A. Mehlman, “An approach to optimal recruitment and transition strategies for manpower systems using dynamic programming”, Journal of Operational Research Society, 31:11 (1980), 1009–1015 | DOI

[3] R. Pastor, J. Olivella, “Selecting and adapting weekly work schedules with working time accounts. A case of a retail clothing chain”, European Journal of Operational Research, 184:1 (2008), 1–12 | DOI

[4] J. W. Forrester, Industrial Dynamics, MIT Press, Cambridge, MA, 1973

[5] T. Kok, F. Janssen, J. Doremalen, E. Wachem, M. Clerkx, W. Peeters, “Philips Electronics Synchronizes its Supply Chain to End the Bullwhip Effect”, Interfaces, 35:1 (2005), 37–48 | DOI

[6] C. D. Tarantilis, “Editorial: Topics in Real-time Supply Chain Management”, Computers Operations Research, 35 (2008), 3393–3396 | DOI

[7] E. S. Bres, D. Burns, A. Charnes, W. W. Cooper, “A Goal Programming model for planning officer accessions”, Management Science, 26:8 (1980), 773–783 | DOI

[8] E. Semenkin, M. Semenkina, “Self-configuring Genetic Algorithm with Modified Uniform Crossover Operator”, Advances in Swarm Intelligence, Lecture Notes in Computer Science, 7331, eds. Y. Tan, Y. Shi, Z. Ji, Springer-Verlag, Berlin–Heidelberg, 2012, 414–421 | DOI

[9] E. Semenkin, M. Semenkina, “Self-Configuring Genetic Programming Algorithm with Modified Uniform Crossover”, Proceedings of the Congress on Evolutionary Computations of the IEEE World Congress on Computational Intelligence, CEC WCCI 2012 (Brisbane, Australia, 2012), 1918–1923

[10] E. Semenkin, M. Semenkina, “The Choice of Spacecrafts' Control Systems Effective Variants with Self-Configuring Genetic Algorithm”, Informatics in Control. Automation and Robotics, Proceedings of the 9th International Conference ICINCO, v. 1, eds. J. L. Ferrier et al., 2012, 84–93

[11] E. Semenkin, M. Semenkina, “Stochastic Models and Optimization Algorithms for Decision Support in Spacecraft Control Systems Preliminary Design”, Informatics in Control, Automation and Robotics, Lecture Notes in Electrical Engineering, 283, eds. J.-L. Ferrier et al., Springer International Publishing Switzerland, 2014, 51–65 | DOI

[12] A. Škraba, E. Semenkin, M. Semenkina, D. Kofjač, A. Žnidaršič, Č. Rozman, M. Maletič, Sh. Akhmedova, V. Stanovov, “Development of discrete manpower model and determination of optimal control strategies”, Proceedings of the XVIII International Scientific Conference “Reshetnev Readings” (2014), 421–423