A simulation-based optimisation approach for inventory management of highly perishable food

The taste and freshness of perishable foods decrease dramatically with time. Effective inventory management requires understanding of market demand as well as balancing customers needs and preferences with products' shelf life. The objective is to avoid food overproduction as this leads to waste and value loss. In addition, product depletion has to be minimised, as it can result in customers reneging. This study tackles the production planning of highly perishable foods (such as freshly prepared dishes, sandwiches and desserts with shelf life varying from 6 to 12 hours), in an environment with highly variable customers demand. In the scenario considered here, the planning horizon is longer than the products' shelf life. Therefore, food needs to be replenished several times at different intervals. Furthermore, customers demand varies significantly during the planning period. We tackle the problem by combining discrete-event simulation and particle swarm optimisation (PSO). The simulation model focuses on the behaviour of the system as parameters (i.e. replenishment time and quantity) change. PSO is employed to determine the best combination of parameter values for the simulations. The effectiveness of the proposed approach is applied to some real-world scenario corresponding to a local food shop. Experimental results show that the proposed methodology combining discrete event simulation and particle swarm optimisation is effective for inventory management of highly perishable foods with variable customers demand.