Novel Route Planning System for Machinery Selection. Case: Slurry Application

Abstract

The problem of finding an optimal solution for the slurry application process is casted as a capacitated vehicle routing problem (CVRP) in which by considering the vehicle’s capacity, it is required to visit all the tracks only once to fully cover the field, as well as complying with a specified targeted application rate. A key objective in this study was to determine an optimized coverage plan in order to minimize the driving distance in the field, while at the same time allowing for varying the application rate. The coverage plan includes the optimal sequence of tracks with a specified application rate for each track. Two algorithms were developed for optimization and simulation of the slurry application cast as capacitated operations. In order to validate the proposed algorithms, a slurry application operation was recorded, and the results of the optimization algorithm were compared with the conventional non-optimized method. The comparison showed that applying the proposed new method reduces the non-working distance by 18.6% and the non-working time by 28.1%.

Route Planning for Agricultural Machines with Multiple Depots: Manure Application Case Study

“…Simulated annealing (SA) as a stochastic algorithm is used in this study to investigate the near-optimal solution. This method has been implemented in several problems in various fields such as computer design, route planning, and image processing [6,28,29]. The mechanism of this algorithm is based on the simulation of a cooling process called annealing where a solid is gradually cooled.…”

“…Therefore, more efforts are being contributed to the development of advanced information and communication technology (ICT) systems and operation management tools to achieve higher operational efficiency and machinery productivity [4]. These tools/systems have been developed ranging from aiding and supporting navigation efforts to full autosteering systems [5][6][7][8]. Most of these systems can navigate and supervise the operator to complete the field tasks by setting the route for a vehicle either manually or using a predefined fieldwork pattern.…”

“…Concerning this problem, advanced methods based on combinatorial optimization have recently been introduced based on one or multiple optimization criteria that include the minimization of the total nonworking traveled distance [11], total operational time [12], and soil compaction risk [13,14]. All of these algorithms used the metaheuristic algorithms (i.e., Clarke-Wright savings algorithm [15,16], genetic algorithm [17,18], simulated annealing algorithm [6,19], ant colony algorithm [20,21]) to find optimal or near-optimal solutions in a reasonable time. The reason is that the route planning problem is considered as a non-deterministic polynomial (NP-hard) combinatorial optimization problem, and exact algorithms tend to perform poorly in the case of large-size instances [22].…”

Row End Detection and Headland Turning Control for an Autonomous Banana-Picking Robot

“…By applying the meta-heuristic algorithm, the optimal traversal sequence of fieldwork tracks under the criterion of minimizing the non-working traveled distance during the headland turnings was found. Moreover, a simulation model was designed to generate the traveled distance of the operation [22]. One of the major disadvantages of the numerical optimization method is the high computational time, which is the key factor in real-time applications.…”

In-Field Performance of Biomass Balers

“…Assessment of machinery and operator costs could be estimated for each field, or subsection, instead of using some type of aggregated average. Applying conventional machinery management models with DGPS data for round baling operations provides the basis for analysis and simulation of the harvest of high-yielding bioenergy crops [10][11][12].…”