Title: An inventory model for continuously deteriorating agri-fresh produce: an artificial immune system-based solution approach

Authors: Manish Shukla; Sanjay Jharkharia

Addresses: Malaysia Institute for Supply Chain Innovation, Shah Alam, Selangor 40150, Malaysia ' Quantitative Methods and Operations Management Area, Indian Institute of Management Kozhikode, IIM Kozhikode Campus, Kunnamangalam, Kozhikode (Kerala) 673570, India

Abstract: 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.

Keywords: agri-fresh produce; inventory management; replenishment policy; AIS; artificial immune systems; metaheuristics; inventory modelling; continuously deteriorating items; wholesale markets; stochastic demand; periodic review; lost sales; inventory retrieval; perishable goods; fresh produce wholesalers.

DOI: 10.1504/IJISM.2014.064362

International Journal of Integrated Supply Management, 2014 Vol.9 No.1/2, pp.110 - 135

Received: 10 May 2013
Accepted: 27 May 2014
Published online: 19 Aug 2014 *

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