Optimization of operational cost planning in integrated farming systems using a mixed-integer linear programming approach - Lasker Pangarapan Sinaga; Rizki Habibi; Suvriadi Panggabean (State Islamic University of North Sumatra, 2026)
This study addresses the challenge of optimizing small-scale integrated farming systems (IFS) by minimizing operational costs while ensuring sustainable land use across agricultural, livestock, and aquaculture components. The main objective is to develop a Mixed-Integer Linear Programming (MILP) model that incorporates deterministic parameters such as land availability, labor allocation, and internal-external input flows. The model integrates multiple interrelated subsystems using production coefficients, resource constraints, and cost structures derived from actual smallholder scenarios. A two-period simulation was conducted to evaluate the model’s effectiveness using fixed input values, reflecting rural farming conditions. The results demonstrate that the system achieved consistent outputs without requiring external purchases of manure, feed, or irrigation water. The total operational cost reached IDR 96,770,000, with optimized land and labor allocation across periods. This research contributes a novel MILP formulation tailored to integrated farming, providing practical insights for policymakers and practitioners. Its implications extend to the development of decision-support systems for rural agricultural planning. However, the model's deterministic assumption limits its adaptability to dynamic environments. Future work should explore stochastic variants and real-time input adjustments to improve model flexibility and realism.