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Student Project | Computer Science | Volume 15 Issue 4, April 2026 | Pages: 1 - 10 | India
Optimizehub: Evolutionary Algorithm Platform
Abstract: There's a significant problem in the optimization field today. While evolutionary algorithms have proven themselves capable of solving incredibly complex computational problems, most people who could benefit from them simply can't access them. Why? The answer usually comes down to two things: money and expertise. Commercial optimization software demands both substantial financial investment and specialized technical knowledge. The open-source alternatives that exist aren't much better- they typically require complicated installation processes and significant programming skills. This accessibility problem hits three groups particularly hard: educational institutions trying to teach optimization concepts, individual researchers working with limited budgets, and small businesses that need optimization solutions but can't justify enterprise-level software costs. Our response to this problem is OptimizeHub, a platform you can access through any web browser. We built it entirely using open-source technologies. The system lets users work on optimization problems with five to twenty decision variables using five different metaheuristic approaches: Genetic Algorithm, Particle Swarm Optimization, Differential Evolution, Simulated Annealing, and Ant Colony Optimization for continuous domains. We've designed the platform around two core principles: security through containerized execution, and usability through intuitive result visualization. What we're really trying to do here is show how modern web technologies can make sophisticated optimization techniques available to everyone, while still maintaining security and working within reasonable computational limits.
Keywords: optimization, evolutionary algorithms, web platform, open source, genetic algorithm, particle swarm optimization, differential evolution, simulated annealing, ant colony optimization
How to Cite?: Sanjana M Nagaraj, Ahana Srinath Murthy, Shruthi Srinivas, Siriganga RB, Thendral Kabilan, "Optimizehub: Evolutionary Algorithm Platform", Volume 15 Issue 4, April 2026, International Journal of Science and Research (IJSR), Pages: 1-10, https://www.ijsr.net/getabstract.php?paperid=SR26328113345, DOI: https://dx.dx.doi.org/10.21275/SR26328113345