Abstract
Capacitated field operations involve input/output material flows where there are capacity constraints in the form of a specific load that a vehicle can carry. As such, a specific normal-sized field cannot be covered in one single operation using only one load, and the vehicle needs to get serviced (i.e., refilling) from out-of-field facilities (depot). Although several algorithms have been developed to solve the routing problem of capacitated operations, these algorithms only considered one depot. The general goal of this paper is to develop a route planning tool for agricultural machines with multiple depots. The tool presented consists of two modules: the first one regards the field geometrical representation in which the field is partitioned into tracks and headland passes; the second one regards route optimization that is implemented by the metaheuristic simulated annealing (SA) algorithm. In order to validate the developed tool, a comparison between a well-known route planning approach, namely B-pattern, and the algorithm presented in this study was carried out. The results show that the proposed algorithm outperforms the B-pattern by up to 20.0% in terms of traveled nonworking distance. The applicability of the tool developed was tested in a case study with seven scenarios differing in terms of locations and number of depots. The results of this study illustrated that the location and number of depots significantly affect the total nonworking traversal distance during a field operation.
Highlights
The decreasing marginal income and increasing costs in agriculture require modern agriculture to become increasingly productive [1]
The routing problem in our case is formulated as a capacitated vehicle routing problem with multiple depots (MD-CVRP) that has been extensively studied in an industrial section like logistic planning
The field shapes and machine-related specifications were considered in this work as shown in Table 2, which are used as input data for the optimization algorithm
Summary
The decreasing marginal income and increasing costs in agriculture require modern agriculture to become increasingly productive [1]. The production of large and powerful agricultural machinery has been the main engineering focus of manufacturing sectors to increase productivity and efficiency. 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
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