Optimization of Nonlinear Systems Using Genetic Algorithms: A Case Study in Resource Allocation
DOI:
https://doi.org/10.62951/ijamc.v1i2.72Keywords:
Genetic algorithms, Nonlinear optimization, Resource allocation, Heuristic methods, Computational efficiencyAbstract
This paper explores the use of genetic algorithms (GAs) for optimizing nonlinear systems in resource allocation. By simulating various allocation scenarios, we demonstrate the efficiency of GAs in finding near-optimal solutions in complex environments. The study provides a comparison of GA performance against traditional optimization methods and identifies scenarios where GAs outperform. The results emphasize the utility of GAs in real-world applications, especially when conventional approaches struggle with large solution spaces.
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