Title: Harvest scheduling to reduce waste in agri-fresh produce supply chains: an artificial immune system-based solution approach
Authors: Manish Shukla; Sanjay Jharkharia
Addresses: Malaysia Institute for Supply Chain Innovation, Section U8, Shah Alam, 40150 Selangor, Malaysia ' Quantitative Methods and Operations Management Area, Indian Institute of Management Kozhikode, IIM Kozhikode Campus, Kunnamangalam, Kozhikode (Kerala) 673570, India
Abstract: This paper presents a mathematical model to maximise the overall profit by reducing the waste of agri-fresh produce. This is achieved by synchronising demand with supply through an optimal harvest schedule. The proposed model is complex in nature, and obtaining an optimal solution in practical time limits is extremely difficult. Therefore, we applied a meta-heuristics, artificial immune system (AIS) to obtain (near) optimal solutions. The proposed model was tested on a dataset generated from real-life scenario of Azadpur wholesale market, New Delhi (India). The result shows that the proposed model, when solved with AIS, provides better results as compared to the base policy, which assumes the plantations are harvested as soon as they attain maturity. Performance of the applied algorithm, AIS, is tested by comparing the results obtained by solving the same problem instances with other established algorithms such as simulated annealing (SA) and genetic algorithm (GA).
Keywords: agri-fresh produce; harvest scheduling; artificial intelligence; artificial immune system; AIS; waste reduction; food supply chains; supply chain management; SCM; mathematical modelling; India.
International Journal of Planning and Scheduling, 2014 Vol.2 No.1, pp.14 - 39
Available online: 27 Dec 2014 *Full-text access for editors Access for subscribers Free access Comment on this article