Evolutionary neighborhood discovery algorithm for agricultural routing planning in multiple fields

Abstract

In recent years, operations research in agriculture has improved the harvested yield, reduced the cost and time required for field operations, and maintained economic and environmental sustainability. The heuristics method, named Evolutionary neighborhood discovery algorithm (ENDA), is applied to minimize the inter-field and intra-field distance of the routing planning of machines in multiple agricultural fields. The problem is an extended version of the Agricultural Routing Planning (ARP) that takes into consideration the different capacity of the machines and multiple agricultural fields. This research also describes the mathematical model to represent the proposed problem formulated as an integer program. The experimental results show that ENDA successfully solves ARP instances, giving the best results and the fastest running time compared to those obtained by Genetic Algorithms and Tabu Search. The results also show that ENDA can save an average of 11.72% of the distance traveled by the machines outside the working path (when making maneuvers, going to or from the entrances and going from and returning to the Depot).

Optimal guidance track generation for precision agriculture: A review of coverage path planning techniques

“…Although we concentrate on guidance track generation in this review, a complete picture of the three-step process is nevertheless necessary when the reader is faced with her/ his first CCPP assignment. Therefore we direct the reader to references (Bochtis & Vougioukas, 2008;Hameed et al, 2011;Utamima & Djunaidy, 2021;Utamima et al, 2022Utamima et al, , 2018 to get an overview on route planning techniques, and to (Backman et al, 2015;Fraichard & Scheuer, 2004;Höffmann, Patel, et al, 2022;Rapoport et al, 2021;Ravankar et al, 2018) to tackle the path smoothing step.…”

Integrated Route-Planning System for Agricultural Robots

“….⟩ (Figure 4a). Optimized patterns (B patterns), on the other hand, are algorithmically sequencies of fieldwork tracks based on an optimization process under certain c The case of B patterns was implemented in the present work, a type of optimal pattern produced by the implementation of various vehicle routing problem stances, first presented in [41] and implemented in various works on agricult planning [45][46][47][48][49]. B patterns are generated based on the criterion of minimizing the ing distance travelled by the machine during the field area coverage operation (Fig For any traversal sequence, the total non-working distance traveled by tural machine is given by the following equation:…”

The Optimal Routing of Raspberry Pickers in an Analytical and Simulation Approach

“…There are three well defined research fields in the case of raspberry picking literature. The first research area focuses on optimizing, automating and robotizing berry harvesting processes for example : A Berry Picking Robot With A Hybrid Soft-Rigid Arm: Design and Task Space Control (Uppalapalti et al, 2020); Simulation of Multi-Agent Architectures for Fruit and Berry Picking Robot in Active-HDL (Kiktev et al, 2021); Route optimization in mechanized sugarcane harvesting (Santoro et l., 2017); Optimized routing on agricultural fields by minimizing maneuvering and servicing time (Spekken and Bruin, 2013); Evolutionary neighborhood discovery algorithm for agricultural routing planning in multiple fields Utamima et al, 2022); Route planning for agricultural tasks: A general approach for fleets of autonomous vehicles in site-specific herbicide applications (Conesa-Muñoz et al, 2016).…”