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Autor
Saadouli Nasreddine (Gulf University for Science and Technology, Kuwait)
Tytuł
Stochastic Programming Model for Production Planning with Stochastic Aggregate Demand and Spreadsheet-based Solution Heuristics
Źródło
Operations Research and Decisions, 2021, vol. 31, no. 4, s. 117-127, rys., tab., bibliogr. 23 poz.
Słowa kluczowe
Planowanie produkcji, Programowanie stochastyczne, Podejmowanie decyzji, Algorytmy, Arkusze kalkulacyjne, Heurystyka
Production planning, Stochastic programming, Decision making, Algorithms, Spreadsheets, Heuristics
Uwagi
summ.
Abstrakt
By discretising the stochastic demand, a deterministic nonlinear programming formulation is developed. Then, a hybrid simulation-optimisation heuristic that capitalises on the nature of the problem is designed. The outcome is an evaluation problem that is efficiently solved using a spreadsheet model. The main contribution of the paper is providing production managers with a tractable formulation of the production planning problem in a stochastic environment and an efficient solution scheme. A key benefit of this approach is that it provides quick near-optimal so lutions without requiring in-depth knowledge or significant investments in optimisation techniques and software. (original abstract)
Dostępne w
Biblioteka Główna Uniwersytetu Ekonomicznego w Krakowie
Biblioteka SGH im. Profesora Andrzeja Grodka
Biblioteka Główna Uniwersytetu Ekonomicznego w Katowicach
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Bibliografia
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  7. HEITSCH H., LEOVEY H., ROMISCH W., Are quasi-Monte Carlo algorithms efficient for two-satge stochastic programs? Comput. Optim. Appl., 2016, 65 (3), 567-603.
  8. KAZEMI M.R., HASSANZADEH R., MAHDAVI I., PARGAR F., Applying fuzzy stochastic programming for multi-product multi-time period production planning, J. Ind. Prod. Eng., 2013, 30 (2), 132-147.
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  13. LIN P.-C., UZSOY R., Chance-constrained formulations in rolling horizon production planning: an experimental study, Int. J. Prod. Res., 2016, 54 (13), 3927-3942.
  14. LUCAS C., MIRHASSANI S.A., MITRA G., POOJARI C.A., An application of Lagrangian relaxation to a capacity planning problem under uncertainty, J. Oper. Res. Soc., 2001, 52 (1), 1256-1266.
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  17. PORTEUS A., PORTEUS E.L., Simultaneous capacity and production management of short-life-cycle, produce-to-stock goods under stochastic demand, Manage. Sci., 2002, 48 (3), 399-413.
  18. SETHI S.P., ZHANG H., ZHANG Q., Optimal and hierarchical controls in dynamic stochastic manufacturing systems: a survey, Manuf. Serv. Oper. Manag., 2002, 4 (2), 133-170.
  19. SHAIKH N., PRABHU V., ABRIL D., SANCHEZ D., ARIAS J., RODRIGUEZ E., RIANO G., Kimberly-Clark Latin America builds an optimization-based system for machine scheduling, Interf., 2011, 41 (5), 455-465.
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Cytowane przez
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ISSN
2081-8858
Język
eng
URI / DOI
http://dx.doi.org/10.37190/ord210406
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