Unemployment still affecting families of a country with potential resources and the implementation of government policies have been facing uncertainties, constraints and difficulties for providing jobs. This paper deals on generating new jobs in Angolan's Crustacean industry business through 2050. How stochastic optimization can be applied to create more jobs? Simulation method of forecasting, tree-stage stochastic optimization model considering 10 notable scenarios and belief modeling strategy for managing risks were applied involving two fishery cooperatives representatives in the probabilities assignment to each demand and availability scenarios in stage 2 and stage 3, resulting in expected revenues around 6,248,283,563.47 Kz and 259 new jobs annually in fishing. These results provides 9% more than the business's earnings, expecting to achieve 3,367 new jobs by 2037 and 6,734 new jobs to 2050. This could lead to the sale of 2,158.8 to 4,035.9 tons of crustaceans (striped grant, shrimp, crab, prawn, and lobster) abundant on the coasts of the provinces of Bengo, Benguela, Cabinda, Cuanza Sul, Icólio Bengo, Luanda, Namibe, and Zaire. To this end, mathematical algorithm were also developed for showing the precise, sequential and logical instructions to follow for helping government and decision-makers to achieve the objectives of unemployment rates reduction in Angola.
| Published in | American Journal of Theoretical and Applied Statistics (Volume 14, Issue 6) |
| DOI | 10.11648/j.ajtas.20251406.11 |
| Page(s) | 250-266 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2025. Published by Science Publishing Group |
Stochastic Optimization, Job Generation, Angola’s Crustacean Industry
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APA Style
Simbo, A. R. N. (2025). Stochastic Optimization for Job Generation in Angola’s Crustacean Industry to 2050. American Journal of Theoretical and Applied Statistics, 14(6), 250-266. https://doi.org/10.11648/j.ajtas.20251406.11
ACS Style
Simbo, A. R. N. Stochastic Optimization for Job Generation in Angola’s Crustacean Industry to 2050. Am. J. Theor. Appl. Stat. 2025, 14(6), 250-266. doi: 10.11648/j.ajtas.20251406.11
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Download@article{10.11648/j.ajtas.20251406.11,
author = {Alcides Romualdo Neto Simbo},
title = {Stochastic Optimization for Job Generation in Angola’s Crustacean Industry to 2050
},
journal = {American Journal of Theoretical and Applied Statistics},
volume = {14},
number = {6},
pages = {250-266},
doi = {10.11648/j.ajtas.20251406.11},
url = {https://doi.org/10.11648/j.ajtas.20251406.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20251406.11},
abstract = {Unemployment still affecting families of a country with potential resources and the implementation of government policies have been facing uncertainties, constraints and difficulties for providing jobs. This paper deals on generating new jobs in Angolan's Crustacean industry business through 2050. How stochastic optimization can be applied to create more jobs? Simulation method of forecasting, tree-stage stochastic optimization model considering 10 notable scenarios and belief modeling strategy for managing risks were applied involving two fishery cooperatives representatives in the probabilities assignment to each demand and availability scenarios in stage 2 and stage 3, resulting in expected revenues around 6,248,283,563.47 Kz and 259 new jobs annually in fishing. These results provides 9% more than the business's earnings, expecting to achieve 3,367 new jobs by 2037 and 6,734 new jobs to 2050. This could lead to the sale of 2,158.8 to 4,035.9 tons of crustaceans (striped grant, shrimp, crab, prawn, and lobster) abundant on the coasts of the provinces of Bengo, Benguela, Cabinda, Cuanza Sul, Icólio Bengo, Luanda, Namibe, and Zaire. To this end, mathematical algorithm were also developed for showing the precise, sequential and logical instructions to follow for helping government and decision-makers to achieve the objectives of unemployment rates reduction in Angola.
},
year = {2025}
}
TY - JOUR T1 - Stochastic Optimization for Job Generation in Angola’s Crustacean Industry to 2050 AU - Alcides Romualdo Neto Simbo Y1 - 2025/11/12 PY - 2025 N1 - https://doi.org/10.11648/j.ajtas.20251406.11 DO - 10.11648/j.ajtas.20251406.11 T2 - American Journal of Theoretical and Applied Statistics JF - American Journal of Theoretical and Applied Statistics JO - American Journal of Theoretical and Applied Statistics SP - 250 EP - 266 PB - Science Publishing Group SN - 2326-9006 UR - https://doi.org/10.11648/j.ajtas.20251406.11 AB - Unemployment still affecting families of a country with potential resources and the implementation of government policies have been facing uncertainties, constraints and difficulties for providing jobs. This paper deals on generating new jobs in Angolan's Crustacean industry business through 2050. How stochastic optimization can be applied to create more jobs? Simulation method of forecasting, tree-stage stochastic optimization model considering 10 notable scenarios and belief modeling strategy for managing risks were applied involving two fishery cooperatives representatives in the probabilities assignment to each demand and availability scenarios in stage 2 and stage 3, resulting in expected revenues around 6,248,283,563.47 Kz and 259 new jobs annually in fishing. These results provides 9% more than the business's earnings, expecting to achieve 3,367 new jobs by 2037 and 6,734 new jobs to 2050. This could lead to the sale of 2,158.8 to 4,035.9 tons of crustaceans (striped grant, shrimp, crab, prawn, and lobster) abundant on the coasts of the provinces of Bengo, Benguela, Cabinda, Cuanza Sul, Icólio Bengo, Luanda, Namibe, and Zaire. To this end, mathematical algorithm were also developed for showing the precise, sequential and logical instructions to follow for helping government and decision-makers to achieve the objectives of unemployment rates reduction in Angola. VL - 14 IS - 6 ER -
Department of Mathematic, University November 11th, Cabinda, Angola
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