Optimization of Star Pomfret Feed Production as a Linear Programming Problem Using a Hybrid Wolfe-Differential Evolution Algorithm

Authors

DOI:

https://doi.org/10.47352/jmans.2774-3047.255

Keywords:

differential evolution algorithm, feed production, star pomfret, Wolfe algorithm

Abstract

Star pomfret (Trachinotus blochii) is one of the most sought-after types of marine fish in Indonesia. The production of feed for star pomfret fish is an important factor because it is related to their survival and ability to grow well.  Therefore, formulating the feed formulation for star pomfret (Trachinotus blochii) is very important to minimize feed production costs and ensure the nutritional adequacy of the fish. Therefore, we change the feed for star pomfret fish as a linear programming (LP) problem and solve it using the Hybrid Differential Evolution-Wolfe Algorithm (HWDEA).  HWDEA combines the Wolfe method, which efficiently transforms constraints into a system of linear equations, with the use of the Differential Evolution Algorithm (DEA) to find a global optimization solution, which is a solution that is not trapped in a local minimum.  We improve accuracy and efficiency by using HWDEA to find the optimal solution for this fish feed production. Our HWDEA can also overcome the limitations of traditional methods such as the simplex algorithm.  Thus, we can show that HWDEA successfully reduced feed production costs from 12,353 IDR to 9,035 IDR per kg while maintaining nutritional balance.  We can conclude that the HWDEA method successfully adapted to price fluctuations and raw material availability, allowing it to produce an optimal raw material composition in feed production.  Therefore, HWDEA can be used as an efficient tool to provide significant cost savings for supporting sustainable and profitable fish farming.

References

[1] T. Xiong, X. Mei, Y. Wu, L. Wang, J. Shi, Y. Sui, S. Cai, F. Cai, X. Chen, and C. Fan. (2023). "Insights into nutrition, flavor and edible quality changes of golden pomfret (Trachinotus ovatus) fillets prepared by different cooking methods". Frontiers in Nutrition. 10 : 1227928. 10.3389/fnut.2023.1227928.

DOI: https://doi.org/10.3389/fnut.2023.1227928

[2] K. Hidayat, H. Yulianto, M. Ali, N. M. Noor, and B. Putri. (2019). "Performa pertumbuhan bawal bintang Trachinotus blochii yang dibudidaya dengan sistem monokultur dan polikultur bersama kerang hijau Perna viridis". Depik. 8 (1): 1-8. 10.13170/depik.8.1.12542.

DOI: https://doi.org/10.13170/depik.8.1.12542

[3] M. F. Azima. (2023). "Teknik Pembesaran Ikan Bawal Bintang (Trachinotus blochii)". South East Asian Aquaculture. 1 (1): 16-23. 10.61761/seaqu.1.1.16-23.

DOI: https://doi.org/10.61761/seaqu.1.1.16-23

[4] R. S. Sundari and Y. A. Priyanto. (2017). "Efisiensi penggunaan faktor-faktor produksi pada teknologi pendederan ikan lele (Clarias sp) sangkuriang". Jurnal Teknologi Perikanan dan Kelautan. 7 (2): 199-206. 10.24319/jtpk.7.199-206.

DOI: https://doi.org/10.24319/jtpk.7.199-206

[5] R. A. Kristiawan, A. Budiharjo, and A. Pangastuti. (2019). "Pemanfaatan potensi Azolla microphylla sebagai pakan untuk ikan sidat (Anguilla bicolor)". Depik. 8 (1): 43-51. 10.13170/depik.8.1.12842.

DOI: https://doi.org/10.13170/depik.8.1.12842

[6] N. A. Loekman, W. H. Satyantini, and A. T. Mukti. (2018). "Penambahan Asam Amino Taurin pada Pakan Buatan terhadap Peningkatan Pertumbuhan dan Sintasan Benih Ikan Kerapu Cantik". Jurnal Ilmiah Perikanan dan Kelautan. 10 (2): 112-118. 10.20473/jipk.v10i2.10504.

DOI: https://doi.org/10.20473/jipk.v10i2.10504

[7] R.Storn, and  K. Price. (1997). "Differential evolution–a simple and efficient heuristic for global optimization over continuous spaces". Journal of global optimization, 11, 341-359. 10.1023/a:1008202821328.

DOI: https://doi.org/10.1023/A:1008202821328

[8] W. Febrianti. (2024). "Algoritma Evolusi: Algoritma Genetika dan Evolusi Diferensial (Disertai Implementasi dengan MATLAB)". ITERA Press.

[9] W. Febrianti, K. A. Sidarto, and N. Sumarti. (2021). "Solving some ordinary differential equations numerically using differential evolution algorithm with a simple adaptive mutation scheme". AIP Conference Proceedings. 10.1063/5.0042351.

DOI: https://doi.org/10.1063/5.0042351

[10] W. Febrianti, K. A. Sidarto, and N. Sumarti. (2021). "Solving systems of ordinary differential equations using differential evolution algorithm with the best base vector of mutation scheme". AIP Conference Proceedings. 10.1063/5.0075320.

DOI: https://doi.org/10.1063/5.0075320

[11] W. Febrianti, K. A. Sidarto, and N. Sumarti. (2022). "Approximate Solution for Barrier Option Pricing Using Adaptive Differential Evolution With Learning Parameter". Mendel. 28 (2): 76-82. 10.13164/mendel.2022.2.076.

DOI: https://doi.org/10.13164/mendel.2022.2.076

[12] W. Febrianti, K. A. Sidarto, and N. Sumarti. (2022). "An Approximate Optimization Method for Solving Stiff Ordinary Differential Equations With Combinational Mutation Strategy of Differential Evolution Algorithm". Mendel. 28 (2): 54-61. 10.13164/mendel.2022.2.054.

DOI: https://doi.org/10.13164/mendel.2022.2.054

[13] W. Febrianti, K. A. Sidarto, and N. Sumarti. (2023). "The Combinational Mutation Strategy of Differential Evolution Algorithm for Pricing Vanilla Options and Its Implementation on Data during Covid-19 Pandemic". arXiv.  10.48550/arXiv.2301.09261.

[14] G. D. Uribe-Guerra, D. A. Múnera-Ramírez, and J. D. Arias-Londoño. (2024). "Feed formulation using multi-objective Bayesian optimization". Computers and Electronics in Agriculture. 224. 10.1016/j.compag.2024.109173.

DOI: https://doi.org/10.1016/j.compag.2024.109173

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Published

2025-04-15

How to Cite

[1]
W. Febrianti, G. Putra, C. Syari, and M. N. Abdallah, “Optimization of Star Pomfret Feed Production as a Linear Programming Problem Using a Hybrid Wolfe-Differential Evolution Algorithm”, J. Multidiscip. Appl. Nat. Sci., vol. 5, no. 2, pp. 419–428, Apr. 2025.