OPTIMIZATION IN HEALTHCARE AND COMPUTER SCIENCE: A COMPARATIVE STUDY OF MATHEMATICAL AND BIO-INSPIRED ALGORITHMS
DOI:
https://doi.org/10.63458/ijerst.v3i4.132Keywords:
Optimization Techniques, Mathematical Optimization, Nature-Inspired Algorithms, Healthcare Engineering, Computational Intelligence, Machine Learning, Bioinformatics, Hybrid Optimization, Resource Allocation, Artificial Intelligence, Deep Learning, Metaheuristic AlgorithmsAbstract
Optimization techniques play a critical role in advancing health care engineering and computer science by providing efficient solutions to complex problems. This paper reviews both mathematical and nature-inspired optimization techniques, highlighting their applications in medical diagnosis, treatment planning, resource allocation, and software engineering. Traditional mathematical approaches such as linear programming and dynamic programming are examined alongside bio-inspired algorithms like genetic algorithms, particle swarm optimization, and artificial bee colony algorithms. A comparative analysis of their effectiveness, computational complexity, and real-world implementation is presented.
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Copyright (c) 2025 Dr.Sangeetha RV
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