Dynamic Programming Approach to Production Planning in a Textile Manufacturing Firm in Katsina State

Production planning in Nigerian manufacturing firms is frequently conducted using intuitive and experience-based approaches that fail to optimize resource utilization across multi-period planning horizons. This study employs dynamic programming to develop an optimal multi-period production plan for a textile manufacturing firm in Katsina State, North West Nigeria. Monthly production, inventory, and demand data for three fabric product lines were collected over a 24-month period from company records and supplemented by interviews with the production manager. A recursive dynamic programming formulation is established with monthly production quantity as the decision variable, inventory carryover as the state variable, and total production and inventory holding costs as the objective to minimize over a 12-month planning horizon. The principle of optimality is applied to solve backward from the terminal period. Results indicate that the optimal plan reduces total production and inventory costs by approximately 26 percent relative to the firm's prevailing planning approach, primarily by smoothing production levels across months to exploit capacity more uniformly and reduce peak-period overtime costs. The study also models the effect of demand uncertainty using stochastic dynamic programming under three demand scenarios. Recommendations include implementing the dynamic programming model as a quarterly planning tool and investing in production scheduling software that accommodates multi-period optimization. This research illustrates the value of dynamic programming in addressing production planning inefficiencies within Nigeria's manufacturing sector. Keywords: dynamic programming, production planning, textile manufacturing, Katsina State, multi-period optimization