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Dear Colleagues,

The use of precision operation technology and intelligent equipment in fields is the frontier of modern agricultural technology development, as the implementation of this equipment has led to the conception of adjusting measures to local conditions, the intelligent management of crop production, the maximization of the production potential of farmland, and the efficient utilization of the key factors in agricultural production and ecological environment protection. In recent years, experts have conducted much research on the interaction mechanism of crops, soil, and other environmental factors, which has caused the rapid acquisition of information, and a precise control model of crop production and intelligent equipment has been developed that uses modern information and intelligent control technology. These remarkable achievements have played an important role in updating traditional agriculture and developing modern agriculture with values of high yields, high quality, high efficiency, ecology, and safety.

This Special Issue will welcome papers that present research on the use of precision operation technology and intelligent equipment in fields. Specific topics include, but are not limited to:

Agricultural sensing mechanisms and new sensors;
Machine–soil–crop interaction mechanisms;
Crop production control models;
New agricultural equipment and field robots;
Intelligent control of agricultural machinery;
Unmanned operations.

Prof. Dr. Jun Ni
Dr. Lei Feng
Dr. Lvhua Han
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agronomy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Related Special Issue

Published Papers (1 paper)

Research

20 pages, 2129 KiB

Open AccessArticle

Task Allocation of Multi-Machine Collaborative Operation for Agricultural Machinery Based on the Improved Fireworks Algorithm

by Suji Zhu, Bo Wang, Shiqi Pan, Yuting Ye, Enguang Wang and Hanping Mao

Agronomy 2024, 14(4), 710; https://0-doi-org.brum.beds.ac.uk/10.3390/agronomy14040710 - 28 Mar 2024

Viewed by 393

Abstract

Currently, the multi-machine collaboration of agricultural machinery is one of the international frontiers and a topic of research interest in the field of agricultural equipment. However, the multi-machine cooperative operation of agricultural machinery is mostly limited to the research on task goal planning and cooperative path optimization of a single operation. To address the mentioned shortcomings, this study addresses the problem of multi-machine cooperative operation of fertilizer applicators in fields with different fertility and fertilizer cooperative distribution of fertilizer trucks. The research uses the task allocation method of a multi-machine cooperative operation of applying fertilizer-transporting fertilizer. First, the problems of fertilizer applicator operation and fertilizer truck fertilizer distribution are defined, and the operating time and the distribution distance are used as optimization objectives to construct functions to establish task allocation mathematical models. Second, a Chaos–Cauchy Fireworks Algorithm (CCFWA), which includes a discretized decoding method, a population initialization with a chaotic map, and a Cauchy mutation operation, is developed. Finally, the proposed algorithm is verified by tests in an actual scenario of fertilizer being applied in the test area of Jimo District, Qingdao City, Shandong Province. The results show that compared to the Fireworks Algorithm, Genetic Algorithm, and Particle Swarm Optimization, the proposed CCFWA can address the problem of falling into a local optimum while guaranteeing the convergence speed. Also, the variance of the CCFWA is reduced by more than 48% compared with the other three algorithms. The proposed method can realize multi-machine cooperative operation and precise distribution of seeds and fertilizers for multiple seeding-fertilizer applicators and fertilizer trucks. Full article

(This article belongs to the Special Issue Precision Operation Technology and Intelligent Equipment in Farmland—2nd Edition)

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