Effects of application costs on fertilizer application strategy

Abstract

Abstract To optimize production activities, it is important to understand the associated costs. If the optimization is carried out using mathematical instruments, the production costs are implemented in the form of a restriction. The functional form is critical not only to ensure accuracy but also to facilitate computing power and input data requirements. The present study documents the development of a cost function for fertilizer application. Three potential ways to address transportation costs within the whole cost function are observed: (i) calculating minimal transportation time using a “split delivery vehicle routing problem” (SDVRP), (ii) estimating transportation time using a regression model, and (iii) neglecting transport costs altogether. In Section 3 , the costs of fertilizer application and their influence on the fertilizer application strategy are compared. Despite minimal differences in the application cost values, all methods lead to comparable results. A further investigation reveals additional factors that influence the reliability of decision-making, for example, price relations. The computational power and data input demands are explored as well. In this respect, the SDVRP method was identified as the most resource-demanding option. We conclude that the performance of the regression method is the most reliable for optimizing the fertilizer application strategy using mathematical instruments. The present study may support researchers focusing on farm logistics or related cost functions, such as spraying, sowing or manure application.