When it comes to today's business environment, especially in the operations-centered industry, the most important goal is to improve the roster of activities and serve those operations in the most efficient manner possible. Powered by data Modern optimization algorithms in combination with models based on production factors have been proved to be useful in the manufacturing business for optimizing production schedules and increasing profitability. We have constructed time and cost models based on real-world data that we have collected. Make use of the information provided to determine the most effective solution to the Job-Shop Scheduling Problem utilizing three algorithms: particle filter, particle swarm optimization, and the genetic algorithm (if applicable). When we want to create operational rosters that are based on a combination of time and cost optimization, the method comes in handy.