Field path planning using capacitated arc routing problem

Duration of Agricultural operations is a crucial issue in fleet management as it directly affects the operation costs. Agricultural fleet usually traverses paths, covering the whole field to complete the operation. The agricultural operations are not necessarily performed efficiently due to the various variables including field shape, presence of obstacles in the field, number of vehicles, and their specifications. In this study, agricultural operations are modeled as a capacitated arc routing problem (CARP). CARP is a combinatorial optimization problem, which determines the harvest paths in a field and finds the best order of traversing. By dividing the paths into two categories of required and non-required, CARP demonstrates a field as a graph. Using CARP, no extra or invalid edge on the graph would be needed. As CARP is an NP-Hard problem, a solution algorithm based on adaptive large neighborhood search (ALNS) is employed to solve large instances of the problem under study. The proposed ALNS algorithm is applied to well-known problem instances as well as a realistic case study to achieve the optimal harvesting pattern efficiently. The computational results demonstrate that the ALNS algorithm surpasses the conventional harvesting pattern. The amount of improvement obtained by the proposed method could vary due to the several factors, including the depot location, vehicle capacity, and field shape.