Hybrid Flowshop Scheduling In Plastic Factory: A Case Study Of Scancom Vietnam Company

Abstract

Scheduling are essential tools for improving efficiency, productivity, and competitiveness in the industrial industry. It is important to take steps to prevent interrupted in an inevitable aspect of real-world production systems, which can disrupt the scheduling process, leading to reduced system efficiency, increased production costs, and potential delivery delays. To address this flexible scheduling problem, we propose GA, PSO and a hybrid PSO-GA algorithm, which combines the exploration capability of Particle Swarm Optimization with the exploitation power of Genetic Algorithm. This research focuses on the development and implementation of an efficient scheduling algorithm that aims to minimize makespan and total completion time in a hybrid flowshop environment in real case study of ScanCom company. The findings of this research provide improved scheduling methods for practical applications. The proposed approach is consider to optimize their production processes, enhance factory performance. By having a well-organized schedule in place, manufacturers can promptly reallocate resources, adjust priorities, and minimize the impact of disruptions on overall production