An inventory model for continuously deteriorating agri–fresh produce: an artificial immune system–based solution approach. (20th August 2014) - Shukla, Manish; Jharkharia, Sanjay
This paper presents an inventory model for managing the continuously deteriorating agri–fresh produce in unorganized wholesale market. Replenishment policy is proposed assuming stochastic demand, periodic review and lost sales. Three inventory retrieval options namely first–in–first–out (FIFO), last–in–first–out (LIFO), and random retrieval (RR) are compared for the proposed replenishment policy. Considering the high problem complexity, artificial immune system (AIS)–based solution methodology is applied and tested on a new dataset generated from real life problem scenario. Results show that the proposed model can be used by wholesalers to efficiently manage the inventory of agri–fresh produce. Results also show that LIFO may be a better policy for produce which are highly perishable and have lower margins. Additionally, RR policy proved to be satisfactory irrespective of the produce characteristics. AIS outperformed when compared with the results obtained by commonly used algorithms such as genetic algorithm (GA) and simulated annealing (SA) for same problem instances.