Citation: Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 15, pages 233â€“236 (2018)
Abstract. €”Every organization and factory optimize their production process with a help of workforce planing. The aim is minimization of the assignment costs of the workers, who will do the jobs. The problem is very complex and needs exponential number of calculations, therefore special algorithms are developed to be solved. The problem is to select employers and to assign them to the jobs to be performed. This problem has very strong constraints and it is difficult to find feasible solutions. The objective is to fulfil the requirements and to minimize the assignment cost. We propose a hybrid Ant Colony Optimization (ACO) algorithm to solve the workforce problem, which is a combination between ACO and an appropriate local search procedure.
- Alba E., Luque G., Luna F., Parallel Metaheuristics for Workforce Planning, J. Mathematical Modelling and Algorithms, Vol. 6(3), Springer, 2007, 509-528.
- Albayrak G., zdemir ., A state of art review on metaheuristic methods in time-cost trade-off problems, International Journal of Structural and Civil Engineering Research, Vol. 6(1), 2017, 30-34.
- Bonabeau E., Dorigo M. and Theraulaz G., Swarm Intelligence: From Natural to Artificial Systems, New York,Oxford University Press, 1999.
- Campbell G., A two-stage stochastic program for scheduling and allocating cross-trained workers, J. Operational Research Society 62(6), 2011, 10381047.
- Dorigo M, Stutzle T., Ant Colony Optimization, MIT Press, 2004.
- Easton F., Service completion estimates for cross-trained workforce schedules under uncertain attendance and demand, Production and Operational Management 23(4), 2014, 660675.
- Fidanova S., Roeva O., Paprzycki M., Gepner P., InterCriteria Analysis of ACO Start Startegies, Proceedings of the 2016 Federated Conference on Computer Science and Information Systems, 2016, 547-550.
- Fidanova S., Luquq G., Roeva O., Paprzycki M., Gepner P., Ant Colony Optimization Algorithm for Workforce Planning, FedCSISâ€™2017, IEEE Xplorer, IEEE catalog number CFP1585N-ART, 2017, 415-419.
- Glover F., Kochenberger G., Laguna M., Wubbena, T. Selection and assignment of a skilled workforce to meet job requirements in a fixed planning period. In:MAEB04, 2004, 636641.
- Grzybowska K., Kovcs, G., Sustainable Supply Chain - Supporting Tools, Proceedings of the 2014 Federated Conference on Computer Science and Information Systems, Vol. 2, 2014, 13211329.
- Hewitt M., Chacosky A., Grasman S., Thomas B., Integer programming techniques for solving non-linear workforce planning models with learning, European J of Operational Research 242(3),2015, 942950.
- Hu K., Zhang X., Gen M., Jo J., A new model for single machine scheduling with uncertain processing time, J Intelligent Manufacturing, Vol 28(3), Springer, 2015, 717-725.
- Li G., Jiang H., He T., A genetic algorithm-based decomposition approach to solve an integrated equipment-workforce-service planning problem, Omega, Vol. 50, Elsevier, 2015, 117.
- Li R., Liu G., An uncertain goal programming model for machine scheduling problem. J. Inteligent Manufacturing, Vol. 28(3), Springer, 2014, 689-694.
- Mucherino A., Fidanova S., Ganzha M., Introducing the environment in ant colony optimization, Recent Advances in Computational Optimization, Studies in Computational Intelligence, Vol. 655, 2016, 147158.
- Ning Y., Liu J., Yan L., Uncertain aggregate production planning, Soft Computing, Vol. 17(4), Springer, 2013, 617624.
- Othman M., Bhuiyan N., Gouw G., Integrating workersâ€™ differences into workforce planning, Computers and Industrial Engineering, Vol. 63(4), 2012, 10961106.
- Parisio A, Jones CN., A two-stage stochastic programming approach to employee scheduling in retail outlets with uncertain demand, Omega, Vol. 53, Elsevier, 2015, 97-103.
- Roeva O., Atanassova V., Cuckoo search algorithm for model parameter identification, Int. J. Bioautomation, Vol. 20(4), 2016, 483492.
- Soukour A., Devendeville L., Lucet C., Moukrim A., A Memetic algorithm for staff scheduling problem in airport security service, Expert Systems with Applications, Vol. 40(18), 2013, 75047512.
- Tilahun S.L., Ngnotchouye J.M.T., Firefly algorithm for discrete optimization problems: A survey, Journal of Civil Engineering, Vol. 21(2), 2017, 535545.
- Toimil D., Gmes A., Review of metaheuristics applied to heat exchanger network design, International Transactions in Operational Research, Vol. 24(1-2), 2017, 726.
- Yang G., Tang W., Zhao R., An uncertain workforce planning problem with job satisfaction, Int. J. Machine Learning and Cybernetics, Springer, 2016. http://dx.doi.org/10.1007/s13042-016-0539-6 http://rd.springer.com/article/10.1007/s13042-016-0539-6
- Zhou C., Tang W., Zhao R., An uncertain search model for recruitment problem with enterprise performance, J Intelligent Manufacturing, Vol. 28(3), Springer, 2014, 295-704. http://dx.doi.org/10.1007/s10845-014-0997-1