Moringa Leaf Powder Production Planning using Mixed-Integer Linear Programming
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Production requirements
Represent weekly demand, processing decisions, capacity, and inventory conditions.
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MILP model
Minimise total production and inventory cost while satisfying every customer demand.
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Branch and bound
Solve the integer planning model in R over a twelve-week horizon.
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Cost-saving plan
Compare optimised schedules with unplanned production under low and high inventory costs.
The problem
Moringa leaf-powder producers must meet customer demand while coordinating production and inventory. Unplanned scheduling can create avoidable costs, especially as operations and inventory become more complex for medium and large businesses.
Who benefits:
- Moringa leaf-powder producers
- Small and medium agro-processing businesses
- Production and inventory planners
- Agricultural supply-chain researchers
Method
A mixed-integer linear programming model minimises production and inventory cost while satisfying all customer demand. The model is solved with a branch-and-bound algorithm implemented in R for a twelve-week horizon. Two simulated cases represent low inventory cost at a university production setting and higher inventory cost in a medium or large business.
Results
Optimised planning reduces total production cost by 7.06% compared with unplanned production in the low-inventory-cost case and by 14.30% in the high-cost case. The approach is especially useful for medium and large businesses with more complex processes and costs, provided the model assumptions and operational constraints are satisfied.
