Abstract
The profitability of the livestock industry largely depends on cost-effective feed formula as feed accounts for a large proportion of production costs. Recently, it is one of research hotspots that investigation on how to scientifically formulate livestock feed reducing the cost. In this work, an Improved Tabu Search (ITS) algorithm is proposed to study the pig feed formula optimization method. The proposed ITS algorithm focuses on combination of the tabu search algorithm and intelligent optimization algorithms, which can obtain advantages of global and local optimization search from traditional optimization algorithms. The experimental results show that the ITS algorithm can achieve higher precision search and performs better than other optimization algorithms.
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Acknowledgements
This work was supported by the National Natural Science Foundation of China (NO. 61602209), Jinan University Funding (NO. JG2020145) and National College Students’ Innovation and Entrepreneurship Training Program (NO. 202110559016).
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Zhang, X., Shen, H., Wu, Z. (2021). Feed Formula Optimization Based on Improved Tabu Search Algorithm. In: Zhang, H., Yang, Z., Zhang, Z., Wu, Z., Hao, T. (eds) Neural Computing for Advanced Applications. NCAA 2021. Communications in Computer and Information Science, vol 1449. Springer, Singapore. https://doi.org/10.1007/978-981-16-5188-5_32
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DOI: https://doi.org/10.1007/978-981-16-5188-5_32
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