Joint pricing and lot-sizing for a perishable item under two-level trade credit with multiple demand classes - Otrodi, F.; Ghasemy Yaghin, R.; Torabi, S. Ali (Computers & industrial engineering, 2019)
•Integrating pricing and lot-sizing for a perishable item under two-level trade credit with multiple demand classes.•Developing a possibilistic bi-objective model for joint pricing and lot-sizing decisions.•Dependency of deterioration rate on the time and temperature changes.•Proposing switching cost constraints to prevent the occurrence of cannibalization in market-segmented pricing.•Developing an efficient search procedure based on the model’s mathematical properties. This paper addresses the differential pricing and lot-sizing problem for a perishable item with multiple demand classes under a two-level trade credit. The distributer sells a single perishable product at different prices to various markets and offers a varied credit period to customers. In the proposed model: (1) the demand rate at each market depends on the selling price, credit period and the price of other complementary and substitute products and (2) the time and temperature parameters affect the deterioration rate. A bi-objective model is developed, which aims to jointly maximize the total profit and minimize the total inventory to assess the supply chain’s inventory performance with multiple demand classes under switching cost constraints. Since most of the parameters are imprecise in nature, a tailored possibilistic programming method based upon the fuzzy measure Me is devised to construct the deterministic counterpart. Several theoretical results are derived which demonstrate the existence and uniqueness of the solution. An efficient search procedure based on the model’s properties is developed to find the pricing and lot-sizing decisions. Then, an efficient multi-objective programming method is used to find efficient compromise solutions. Finally, illustrative examples along with a number of sensitivity analyses are provided to show applicability of the proposed approach and study the influence of key parameters on the model’s performance.