Coverage planning for capacitated field operations under spatial variability Online publication date: Thu, 23-Jul-2015
by Gareth Edwards; Martin Andreas Falk Jensen; Dionysis D. Bochtis
International Journal of Sustainable Agricultural Management and Informatics (IJSAMI), Vol. 1, No. 2, 2015
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.
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