Harvest scheduling to reduce waste in agri-fresh produce supply chains: an artificial immune system-based solution approach. (1st January 2014)

• Record Type: Journal Article
• Authors: Shukla, Manish; Jharkharia, Sanjay
• Is Part Of: International journal of planning and scheduling. Volume 2:Number 1(2014)
• Page Start: 14
• Page End: 39
• Publication Date: 2014-01-01
• Subjects: agri-fresh produce -- harvest scheduling -- artificial intelligence -- artificial immune system -- AIS; Production scheduling -- Periodicals; Mathematical statistics -- Periodicals; Operations research -- Periodicals; 658.53
• DOI: 10.1504/IJPS.2014.066689
• Languages: English
• ISSNs: 2044-494X

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).