Manpower Planning with Annualized Hours Flexibility : a Fuzzy Mathematical Programming Approach

• Autorzy: Gulzarul Hasan , S. Suhaib Hasan
• Języki publikacji: EN

Abstrakty

EN

We have considered the problem of annualized hours (AH) in workforce management. AH is a method of distributing working hours with respect to the demand over a year. In this paper, the basic Manpower planning problem with AH flexibility is formulated as a fuzzy mathematical programming problem with flexible constraints. Three models of the AH planning problem under conditions of fuzzy uncertainty are presented using different aggregation operators. These fuzzy models soften the rigidity of the deterministic model by relaxing some constraints with the use of flexible programming. Finally, an illustration is given with a computational experiment performed on a realistic-scale case problem of an automobile company to demonstrate and analyze the effectiveness of the fuzzy approach over a deterministic model.(original abstract)

Słowa kluczowe

EN

Labour force; Flexitime; Mathematical programming

PL

Siła robocza; Elastyczność czasu pracy; Programowanie matematyczne

• Czasopismo: Decision Making in Manufacturing and Services
• Rocznik: 2016
• Tom: 10
• Numer: nr 1/2
• Strony: 5--29

Twórcy

autor

Gulzarul Hasan

• Aligarh Muslim University, India

autor

S. Suhaib Hasan

• Aligarh Muslim University, India

Bibliografia

• Azmat, C. S., & Widmer, M. (2004). A case study of single shift planning and scheduling under annualized hours: A simple three-step approach. European Journal of Operational Research, 153(1), 148-175.
• Azmat, C. S., Hürlimann, T., & Widmer, M. (2004). Mixed integer programming to schedule a single-shift workforce under annualized hours. Annals of Operations Research, 128(1-4), 199-215.
• Bellman, R. E., & Zadeh, L. A. (1970). Decision-making in a fuzzy environment. Management science, 17(4), B-141.
• Cadenas, J. M., & Verdegay, J. L. (2006). A primer on fuzzy optimization models and methods. Iranian Journal of Fuzzy Systems, 3(1), 1-21.
• Campbell, G. M., & Diaby, M. (2002). Development and evaluation of an assignment heuristic for allocating cross-trained workers. European Journal of Operational Research, 138(1), 9-20.
• Corominas, A., & Pastor, R. (2000, August). Manpower planning and scheduling in services with seasonal demand. In I World Conference on Production and Operations Management.
• Corominas, A., & Pastor, R. (2010). Replanning working time under annualised working hours. International Journal of Production Research,48(5), 1493-1515.
• Corominas, A., Lusa, A., & Pastor, R. (2002). Using MILP to plan annualised working hours. Journal of the Operational Research Society, 53(10), 1101-1108.
• Corominas, A., Lusa, A., & Pastor, R. (2004). Planning annualised hours with a finite set of weekly working hours and joint holidays. Annals of Operations Research, 128(1-4), 217-233.
• Corominas, A., Lusa, A., & Pastor, R. (2005). Annualised hours: a real flexibility tool. OR Insight, 18(1), 10-14.
• Corominas, A., Lusa, A., & Pastor, R. (2007). Planning production and working time within an annualised hours scheme framework. Annals of Operations Research, 155(1), 5-23.
• Corominas, A., Lusa, A., & Pastor, R. (2007). Using a MILP model to establish a framework for an annualised hours agreement. European Journal of Operational Research, 177(3), 1495-1506.
• Corominas, A., Lusa, A., & Olivella, J. (2012). A detailed workforce planning model including non-linear dependence of capacity on the size of the staff and cash management. European Journal of Operational Research, 216(2), 445-458.
• Czyzyk J, Mesnier M P, & Mor J J (1998) The NEOS Server. IEEE Journal on Computational Science and Engineering, 5(3), 6875.
• Dolan, E. D. (2001). NEOS Server 4.0 administrative guide. arXiv preprint cs/0107034.
• Grabot, B., & Letouzey, A. (2000). Short-term manpower management in manufacturing systems: new requirements and DSS prototyping. Computers in industry, 43(1), 11-29.
• Gropp, W., & Moré, J. (1997). Optimization environments and the NEOS server. Approximation theory and optimization, 167-182.
• Hertz, A., Lahrichi, N., & Widmer, M. (2010). A flexible MILP model for multiple-shift workforce planning under annualized hours. European Journal of Operational Research, 200(3), 860-873.
• Hung, R. (1999a). A multiple-shift workforce scheduling model under annualized hours. Naval Research Logistics (NRL), 46(6), 726-736.
• Hung, R. (1999b). Scheduling a workforce under annualized hours.International Journal of Production Research, 37(11), 2419-2427.
• Itoh, T., Ishii, H., & Nanseki, T. (2003). A model of crop planning under uncertainty in agricultural management. International Journal of Production Economics, 81, 555-558.
• Tang, J., Wang, D. W., Fung, R. Y., & Yung, K. L. (2004). Understanding of fuzzy optimization: theories and methods. Journal of Systems Science and Complexity, 17(1), 117-136.
• Lai Y. J. and Hwang C. L. (1992) Fuzzy Mathematical Programming Lecture Notes in Economics and Mathematical Systems 394, Springer-Verlag, Berlin.
• Lusa, A., & Pastor, R. (2011). Planning working time accounts under demand uncertainty. Computers & Operations Research, 38(2), 517-524.
• Lusa, A., Corominas, A., & Munoz, N. (2008a). A multistage scenario optimisation procedure to plan annualised working hours under demand uncertainty. International Journal of Production Economics, 113(2), 957-968.
• Lusa, A., Corominas, A., & Pastor, R. (2008b). An exact procedure for planning holidays and working time under annualized hours considering cross-trained workers with different efficiencies. International Journal of Production Research, 46(8), 2123-2142.
• Lusa, A., Corominas, A., Olivella, J., & Pastor, R. (2009). Production planning under a working time accounts scheme. International Journal of Production Research, 47(13), 3435-3451.
• ^ McMeekin, J. (1995). Why Tesco's new composite distribution needed annual hours. International Journal of Retail & Distribution Management,23(9), 36-38.
• Miller, W. A., Leung, L. C., Azhar, T. M., & Sargent, S. (1997). Fuzzy production planning model for fresh tomato packing. International Journal of Production Economics, 53(3), 227-238.
• NEOS Server: State-of-the-Art Solvers for Numerical Optimization, http://www.neos-server.org/neos/, Accessed on 2016 June 21.
• Official site of government- 35-hour workweek, http://travail-emploi.gouv.fr/, Accessed on 2016 June 21.
• Pastor, R., & Corominas, A. (2010). A bicriteria integer programming model for the hierarchical workforce scheduling problem. Journal of modelling in management, 5(1), 54-62.
• Pastor, R., & Olivella, J. (2008). Selecting and adapting weekly work schedules with working time accounts: A case of a retail clothing chain.European Journal of Operational Research, 184(1), 1-12.
• Pendharkar, P. C. (1997). A fuzzy linear programming model for production planning in coal mines. Computers & Operations Research, 24(12), 1141-1149.
• Rabbani, M., Jolai, F., Manavizadeh, N., Radmehr, F., & Javadi, B. (2012). Solving a bi-objective cell formation problem with stochastic production quantities by a two-phase fuzzy linear programming approach. The International Journal of Advanced Manufacturing Technology, 58(5-8), 709-722.
• Rodriguez, M. (2003). Flexible working patterns using annualised hours.Work Study, 52(3), 145-149.
• Selim, H., & Ozkarahan, I. (2008). A supply chain distribution network design model: an interactive fuzzy goal programming-based solution approach. The International Journal of Advanced Manufacturing Technology, 36(3-4), 401-418.
• Sureshkumar, M., & Pillai, V. (2012). Planning annuaulised hours when spike in demand exists. International Journal of Industrial Engineering Computations, 3(3), 313-320.
• Sureshkumar, M. R., & Pillai, V. M. (2013). An efficient method to reduce relative capacity shortage using annualised hours planning. The International Journal of Advanced Manufacturing Technology, 65(1-4), 571-580.
• Tsai, C. C., Chu, C. H., & Barta, T. A. (1997). Modeling and analysis of a manufacturing cell formation problem with fuzzy mixed-integer programming.IIE transactions, 29(7), 533-547.
• Van den Hurk, H. (2007). Arbeidsvoorwaarden in 100 vragen: voor or's en hr-medewerkers. Kluwer.
• Van der Veen, E., Boucherie, R. J., & Van Ommeren, J. C. W. (2012). Optimal staffing under an annualized hours regime using cross-entropy optimization.
• Van der Veen, E., Hans, E. W., Veltman, B., Berrevoets, L. M., & Berden, H. J. (2015). A case study of cost-efficient staffing under annualized hours.Health care management science, 18(3), 279-288.
• Filho, E. V. G., & Marçola, J. A. (2001). Annualized hours as a capacity planning tool in make-to-order or assemble-to-order environment: an agricultural implements company case. Production Planning & Control, 12(4), 388-398.
• Werners, B. (1987). An interactive fuzzy programming system. Fuzzy sets and systems, 23(1), 131-147.
• Wikipedia, the free encyclopedia, 35-hour workweek , Accessed on 2016 June 21.
• Workforce logistics, Annualised hours case study- Thomas Sanderson: , Accessed on 2016 June 21.
• Zadeh, L. A. (1965). Fuzzy sets. Information and control, 8(3), 338-353.
• Zimmermann, H. J. (1975). DESCRIPTION AND OPTIMIZATION OF FUZZY SYSTEMS†. International Journal of General System, 2(1), 209-215.
• Zimmermann, H. J. (1996) Fuzzy Set Theory-and Its Applications (3rd ed.). Boston: Kluwer Academic Publishers.

Identyfikatory

DOI

https://doi.org/10.7494/dmms.2016.10.1-2.5