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Rima Aprilia
Universitas Islam Negeri Sumatera Utara, Sumatera Utara, Indonesia
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Electrical & Electronics Engineering Physics

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Scenario based two stage production planning for cassava SMEs under demand uncertainty Dedy Juliandry Panjaitan; Rima Aprilia; Firmansyah Firmansyah
International Journal of Basic and Applied Science Vol. 14 No. 4 (2026): March: Computer Science
Publisher : Institute of Computer Science (IOCS)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35335/ijobas.v14i4.850

Abstract

Production planning in small and medium sized enterprises (SMEs) is commonly based on deterministic assumptions that do not fully reflect uncertain market demand. This study develops a scenario-based production planning approach to support feasible and cost efficient decisions under demand uncertainty. Two stage stochastic programming model with demand scenarios is applied to a real multi-product SME (small medium enterprises) case, where three demand scenarios pessimistic, most likely, and optimistic are constructed from historical data. The model incorporates production costs, raw material availability, labor capacity, and machine capacity constraints and is solved using a standard linear programming solver with actual operational data. The results indicate that optimal production quantities and total production costs vary across demand scenarios due to differences in demand limits and resource availability. While deterministic planning becomes infeasible under extreme demand conditions, the proposed Two stage stochastic programming model consistently produces feasible and cost efficient production plans, resulting in consistently feasible solutions across all demand scenarios, and highlighting its usefulness as a practical decision support tool  for SMEs facing demand uncertainty.
Co-Authors Dedy Juliandry Panjaitan Firmansyah, Firmansyah