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The present article explores the resource planning problem in a hypothetical steelwork plant using an open-source Optimization via Simulation (OvS) framework. By integrating Discrete Event Simulation (DES) via JaamSim with the OSIRES optimization framework, the researchers address the complex challenge of resource allocation in an industrial setting. Four optimization algorithms were tested: Scatter Search, GRASP, Particle Swarm Optimization (PSO), and Fire-Fly, to maximize the annual net income by determining the optimal quantity and capacity of torpedo cars, cranes, and steel furnaces. Results indicated that the PSO algorithm achieved the best performance, effectively navigating a solution space of 1.2 million possibilities to find a local optimal solution that maximizes the economic configuration. The findings demonstrate that open-source tools provide a robust, transparent, and cost-effective alternative to proprietary software for complex decision-making. This approach supports the transition to Industry 5.0 by fostering resilient and sustainable manufacturing processes through accessible analytical tools.
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