Solving Agricultural Route Planning with Improved Particle Swarm Optimization

This research solves the optimization of agricultural machinery routes to help the agricultural sector make decisions with predetermined constraints. The purpose of Agricultural Route Planning (ARP), is to maximize the efficiency of the path used by agricultural machinery by reducing the amount of distance covered by the machine in headland regions. Particle Swarm Optimization (PSO) algorithm is utilized by representing nodes for each track in a farm field. The finding of the experiments demonstrate that the improved version of PSO is capable of achieving shorter distances than the default configuration of PSO. Moreover, the application of the proposed algorithm is superior to manual operation in terms of performance in the agricultural sector.

[1]  Amir H. Ansaripoor,et al.  Evolutionary neighborhood discovery algorithm for agricultural routing planning in multiple fields , 2022, Annals of Operations Research.

[2]  Amalia Utamima,et al.  A comparative study of hybrid estimation distribution algorithms in solving the facility layout problem , 2021 .

[3]  Kanchana Sethanan,et al.  Hybrid particle swarm optimization and neighborhood strategy search for scheduling machines and equipment and routing of tractors in sugarcane field preparation , 2020, Comput. Electron. Agric..

[4]  Amalia Utamima,et al.  Automation in Agriculture: A Case Study of Route Planning Using an Evolutionary Lovebird Algorithm , 2020, ICCAE.

[5]  Hasan Seyyedhasani,et al.  Routing algorithm selection for field coverage planning based on field shape and fleet size , 2019, Comput. Electron. Agric..

[6]  Richard Alan Peters,et al.  Particle Swarm Optimization: A survey of historical and recent developments with hybridization perspectives , 2018, Mach. Learn. Knowl. Extr..

[7]  Athanasios Migdalas,et al.  A hybrid Particle Swarm Optimization - Variable Neighborhood Search algorithm for Constrained Shortest Path problems , 2017, Eur. J. Oper. Res..

[8]  Hasan Seyyedhasani,et al.  Using the Vehicle Routing Problem to reduce field completion times with multiple machines , 2017, Comput. Electron. Agric..

[9]  Kanchana Sethanan,et al.  Multi-objective particle swarm optimization for mechanical harvester route planning of sugarcane field operations , 2016, Eur. J. Oper. Res..

[10]  Amalia Utamima,et al.  Penyelesaian Masalah Penempatan Fasilitas dengan Algoritma Estimasi Distribusi dan Particle Swarm Optimization , 2016 .

[11]  Harish Garg,et al.  A hybrid PSO-GA algorithm for constrained optimization problems , 2016, Appl. Math. Comput..

[12]  Fuhao Zhang,et al.  A Combination of Genetic Algorithm and Particle Swarm Optimization for Vehicle Routing Problem with Time Windows , 2015, Sensors.

[13]  Graham Kendall,et al.  Search Methodologies: Introductory Tutorials in Optimization and Decision Support Techniques , 2013 .

[14]  Tamas Keviczky,et al.  Complete Field Coverage as a Multi-Vehicle Routing Problem , 2013 .

[15]  Xuhua Yang,et al.  Improved Particle Swarm Optimization For Traveling Salesman Problem , 2013, ECMS.

[16]  Utamima Amalia,et al.  Solving Single Row Facility Layout Problem using Extended Artificial Chromosome Genetic Algorithm , 2012 .

[17]  Zongrong Qin,et al.  Particle Swarm Optimization Algorithm with Real Number Encoding for Vehicle Routing Problem , 2011, 2011 International Conference of Information Technology, Computer Engineering and Management Sciences.

[18]  Claus G. Sørensen,et al.  The vehicle routing problem in field logistics: Part II , 2009 .

[19]  Dionysis Bochtis,et al.  Minimising the non-working distance travelled by machines operating in a headland field pattern , 2008 .

[20]  A. Djunaidy,et al.  Agricultural routing planning: A narrative review of literature , 2022, Procedia Computer Science.

[21]  Amalia Utamima,et al.  Evolutionary Estimation of Distribution Algorithm for Agricultural Routing Planning in Field Logistics , 2019, Procedia Computer Science.

[22]  M A Hannan,et al.  Capacitated vehicle-routing problem model for scheduled solid waste collection and route optimization using PSO algorithm. , 2018, Waste management.

[23]  Torsten Reiners,et al.  The Agricultural Routing Planning in Field Logistics , 2018 .

[24]  John Fulcher,et al.  Computational Intelligence: An Introduction , 2008, Computational Intelligence: A Compendium.