Optimizing washing machine production at Vestel: a matheuristic approach to planning and scheduling

This research presents an optimisation framework, developed with Vestel, a prominent white goods manufacturer, to enhance production planning in their washing machine factory. The proposed model simultaneously optimises decisions on lot sizing, machine scheduling, shift assignments, and workforce planning over a multi-period horizon, subject to constraints such as machine-part compatibility, setup times, capacity limits, and shift regulations, to minimise total cost while meeting demand. To address the computational complexity of the problem, we develop a tailored matheuristic algorithm that yields near-optimal solutions within practical computation times, enabling efficient solution of large-scale instances. In addition, an industry-inspired planning heuristic based on Vestel's practice is implemented as a baseline for benchmarking. The results of the case study demonstrate that the proposed approach achieves up to 19% cost savings compared to the Vestel-inspired heuristic, while delivering solutions with total costs within a few percent of those obtained by a commercial solver. Moreover, unlike the solver, which frequently fails to return feasible solutions for longer horizons, the matheuristic reliably generates high quality solutions across tested dimensions, underscoring both its computational efficiency and scalability. These findings highlight the practical applicability of the integrated model and matheuristic for complex production planning problems in industrial settings.