Various Aggregate Production Planning (APP) models have been proposed in the literature to determine company’s production, inventory and employment levels over a finite time horizon. Majority of them are deterministic with the objective to minimise the relevant cost. Motivated by a real-world automotive supplier, this paper proposes a new fuzzy APP model which considers time required to complete operations in the production and warehouse inventory as the main indicator of the performance. The paper includes uncertainties in relevant parameters including customer demand deviations from expected values and production output, as well as uncertainty in production time, time of safety stock storing in the warehouse and time of preparation for delivery to customers. The uncertain parameters are modelled using fuzzy sets generated using historical data recorded in the supplier or based on experience of a logistics management team. Various experiments are carried out using real-world data collected in the supplier to analyse the impact that uncertainty has on APP. It is demonstrated that the developed fuzzy APP model can shorten the time required to perform the production and warehouse operations and improve the performance of the supplier.
- Aggregate production planning
- Fuzzy optimisation
- Fuzzy sets
- Uncertain customer demand deviation
- Uncertain production output
ASJC Scopus subject areas
- Computer Science(all)