TY - JOUR
T1 - An improved multi-objective brainstorming algorithm with the application of rapeseed germination characteristics optimization
AU - Yang, Yang
AU - Liu, Bai Lin
AU - Wang, Jiang
AU - Chen, Yu Geng
AU - Ren, Yi Lin
N1 - Publisher Copyright:
© 2023 Elsevier B.V.
PY - 2023/6
Y1 - 2023/6
N2 - As one of the most important raw materials for daily edible oil, the annual production and quality of oilseed rape have a great impact on the daily lives of people and the development of the country. The germination quality of rapeseed directly affects the future yield and quality of oilseed rape, and seed germination vigor (SGV) and chlorophyll content (CC) are important factors affecting the quality of rapeseed germination. It is very necessary to make the rapeseeds have optimal germination characteristics and seed germination vigor at the early stage of germination by controlling the combination of each decision variable at the segmented harvest. The two objectives are coupled with each other to form a complex multi-objective optimization problem, which is important in the current research field of the rapeseed problem. To solve this problem, a modified brainstorming optimization algorithm based on OPTICS clustering, named MOPCBSO, is proposed in this study. The algorithm uses optics clustering as a new clustering method, chaotic mutation as a new updating method for individuals, and introduces an elite strategy and a tracking strategy. 19 benchmark test functions and nonparametric tests are adopted to examine the performance of the MOPCBSO compared with other optimization algorithms. The results show that the proposed algorithm has significant advantages over other algorithms in terms of convergence and comprehensiveness, demonstrating the effectiveness of the algorithm improvement. To optimize rapeseed germination characteristics, mathematical models are built, in which, cut-down time, after-ripening time and stubble height are selected as decision variables, while chlorophyll concentration and seed germination vigor in seeds as the target characteristics. The data of oliseed rape field trials were collected from 2020 to 2021 in Huanggang City, Hubei Province. Finally, the optimal solution for the germination characteristics of rapeseeds was obtained by the MOPCBSO, which provided an effective basis for the subsequent rapeseed production experiments.
AB - As one of the most important raw materials for daily edible oil, the annual production and quality of oilseed rape have a great impact on the daily lives of people and the development of the country. The germination quality of rapeseed directly affects the future yield and quality of oilseed rape, and seed germination vigor (SGV) and chlorophyll content (CC) are important factors affecting the quality of rapeseed germination. It is very necessary to make the rapeseeds have optimal germination characteristics and seed germination vigor at the early stage of germination by controlling the combination of each decision variable at the segmented harvest. The two objectives are coupled with each other to form a complex multi-objective optimization problem, which is important in the current research field of the rapeseed problem. To solve this problem, a modified brainstorming optimization algorithm based on OPTICS clustering, named MOPCBSO, is proposed in this study. The algorithm uses optics clustering as a new clustering method, chaotic mutation as a new updating method for individuals, and introduces an elite strategy and a tracking strategy. 19 benchmark test functions and nonparametric tests are adopted to examine the performance of the MOPCBSO compared with other optimization algorithms. The results show that the proposed algorithm has significant advantages over other algorithms in terms of convergence and comprehensiveness, demonstrating the effectiveness of the algorithm improvement. To optimize rapeseed germination characteristics, mathematical models are built, in which, cut-down time, after-ripening time and stubble height are selected as decision variables, while chlorophyll concentration and seed germination vigor in seeds as the target characteristics. The data of oliseed rape field trials were collected from 2020 to 2021 in Huanggang City, Hubei Province. Finally, the optimal solution for the germination characteristics of rapeseeds was obtained by the MOPCBSO, which provided an effective basis for the subsequent rapeseed production experiments.
KW - Agricultural products
KW - Brainstorm optimization
KW - Multi-objective optimization
KW - Rapeseed
KW - Support vector machines regression
UR - http://www.scopus.com/inward/record.url?scp=85153308110&partnerID=8YFLogxK
U2 - 10.1016/j.compag.2023.107865
DO - 10.1016/j.compag.2023.107865
M3 - Article
AN - SCOPUS:85153308110
SN - 0168-1699
VL - 209
JO - Computers and Electronics in Agriculture
JF - Computers and Electronics in Agriculture
M1 - 107865
ER -