Authors: Gareth Edwards; Martin Andreas Falk Jensen; Dionysis D. Bochtis
Addresses: Department of Engineering, Aarhus University, Blichers Allé 20, Postboks 50, 8830, Tjele, Denmark ' R&D Department, CLAAS E-systems Verw. GmbH, Møllevej 11, 2990 Nivå, Denmark ' Department of Engineering, Aarhus University, Blichers Allé 20, Postboks 50, 8830, Tjele, Denmark
Abstract: Operations involving the collection or dispersion of material are executed by machines with a limited capacity that must unload/reload. Furthermore, the spatial variability of yield or demand increases the complexity of the planning for these operations. When there is no knowledge of the spatial variability, or when intelligent machines make adjustments due to real-time conditions, a new intelligent planning system is needed. A real-time planning system is presented that monitors the capacity change and generates an optimal coverage plan for operations. The system was tested on the Lego operations test platform as a prelude to full-scale testing, utilising a colour map to represent the spatial variability. When the demand is known the planning system produced a solution that is 17%, on average, improved from the conventional coverage, in terms of the total travelled distance, while when demand was unknown the improvement in the total travelled distance was 7%, on average.
Keywords: route planning; Lego test platform; real-time optimisation; operations management; coverage planning; capacitated field operations; spatial variability; intelligent planning; total travelled distance; in-field logistics; agricultural machinery; agriculture; capacitated VRP; CVRP; vehicle routing problem; Lego micro-tractors; harvesting.
International Journal of Sustainable Agricultural Management and Informatics, 2015 Vol.1 No.2, pp.120 - 129
Received: 17 Aug 2014
Accepted: 13 Oct 2014
Published online: 22 Jul 2015 *