期刊
APPLIED SOFT COMPUTING
卷 13, 期 11, 页码 4253-4263出版社
ELSEVIER
DOI: 10.1016/j.asoc.2013.07.004
关键词
Multiobjective optimization; Precision agriculture; Variable-rate fertilization (VRF); Fireworks optimization algorithm (FOA); Differential evolution (DE); Hybrid optimization method
资金
- National Natural Science Foundation [613250211, 61105073, 61103140, 61173096, 61020106009]
- Zhejiang Provincial Natural Science Foundation of China [R1110679]
Variable-rate fertilization (VRF) decision is a key aspect of prescription generation in precision agriculture, which typically involves multiple criteria and objectives. This paper presents a multiobjective optimization problem model for oil crop fertilization, which takes into consideration not only crop yield and quality but also energy consumption and environmental effects. For efficiently solving the problem, we propose a hybrid multiobjective fireworks optimization algorithm (MOFOA) that evolves a set of solutions to the Pareto optimal front by mimicking the explosion of fireworks. In particular, it uses the concept of Pareto dominance for individual evaluation and selection, and combines differential evolution (DE) operators to increase information sharing among the individuals. The experimental tests and real-world applications in oil crop production in east China demonstrate the effectiveness and practicality of the algorithm. (C) 2013 Elsevier B.V. All rights reserved.
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