An ILS-VND approach to dynamic pricing of perishable products

Abstract

This paper deals with the problem of setting prices of a perishable product whose demand decreases over time due to its perishable character and its price elasticity. It considers a discrete-time, deterministic model whose decision variables are the order quantity and the dynamic pricing policy (modelled as a series of discrete discounts in specific periods). Given the combinatorial structure of the problem and its non-linear nature, a hybrid Iterated Local Search (ILS) + Variable Neighborhood Descent (VND) metaheuristic approach is proposed. The initial solution for the search is computed using a heuristic which generally finds a good starting solution. The proposed approach is rather flexible and can accommodate many different scenarios. In particular, it has been validated on two scenarios: one involving a two-day horizon, with 1 h unit time and 12 h open/12 h closed cycle, and another one that considers a 48-day horizon, with 6 h unit time and 12/6 h open cycle. The results show that, in both cases, the proposed metaheuristic outperforms Simulated Annealing (SA), achieves a slight improvement over the heuristic, and reaches the optimal solution (verified through complete enumeration) while maintaining low computational costs. It has also been shown that profit increases of almost 20 %, compared to the no-discount policy.