A Constrained K-Means and Nearest Neighbor Approach for Route Optimization in the Bale Collection Problem. Issue 1 (July 2017)

• Record Type: Journal Article
• Authors: Zamar, David S.; Gopaluni, Bhushan; Sokhansanj, Shahab
• Is Part Of: IFAC-PapersOnLine. Volume 50:Issue 1(2017)
• Page Start: 12125
• Page End: 12130
• Publication Date: 2017-07
• Subjects: constraint satisfaction problems -- optimization -- logistics planning -- autonomy -- agriculture; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2017.08.2148
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: The bale collection problem (BCP) appears after harvest operations of agricultural crops. The solution to the BCP is defined by the sequence in which bales, that lie scattered across the field, are collected. 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 algorithm can be incorporated into precision agricultural systems to assist in the planning of routes for loaders and bale wagons. The approach is experimentally tested on a simulated study area like those found in real situations.