A Constrained k-means and Nearest Neighbor Approach for Route Optimization : With an application to the Bale Collection Problem

The bale collection problem (BCP) appears after harvest operations of agricultural crops. Its solution defines the sequence of collecting bales which lie scattered over the field. Current technology on navigation systems in autonomous agricultural vehicles and machines are able to provide accurate data for reliable bale collection planning. This paper presents a constrained k-means algorithm and nearest neighbor approach to the BCP, which minimizes travel time and hence fuel consumption. The constraints imposed on the k-means procedure is not the usual condition that certain groups of objects must be clustered together, but rather that the cluster centers must lie on valid locations, which may be specified as functions or sets of points. The algorithmic route generation provides the basis for a navigation tool dedicated to loaders and bale wagons. The approach is experimentally tested on a simulated study area similar to those found in real situations.