40th International Conference on Production Engineering of Serbia
ICPES 2025
Nis, Serbia, 18-19th september 2025
DYNAMIC FLEXIBLE JOB SHOP SCHEDULING PROBLEM BASED ON GENETIC ALGORITHM
Katarina Brenjo, Aleksandar Jokic, Milica Petrovic
DOI: 10.46793/ICPES25.247B
The increasing frequency and sophistication of cyber-attacks on manufacturing systems demand that scheduling frameworks evolve to include cybersecurity considerations. The integration of dynamic and cybersecurity-related factors into the flexible job shop scheduling problem modelling is essential to better reflect real-world manufacturing conditions. This paper addresses the flexible job shop scheduling problem in a dynamic manufacturing environment, affected by three unexpected disturbances: the arrival of new jobs into the manufacturing system, job cancellations, and machine tool breakdowns. Particularly, some of these disturbances are caused by cyber-attacks targeting manufacturing systems, increasing risks to production and operational reliability. These disturbances have a significant impact on manufacturing efficiency, affecting delivery deadlines, resource utilization, and overall processing time. In this research paper, a genetic algorithm is applied as a robust artificial intelligence technique suitable for solving NP-hard combinatorial problems such as the dynamic flexible job shop scheduling problem. The algorithm facilitates real-time adjustment through rescheduling mechanisms, aiming to achieve a specified optimization objective – minimizing the total processing time (makespan). The proposed method is implemented in the MATLAB® environment and validated through simulations using relevant benchmark problems. Experimental results demonstrate that the proposed methodology significantly improves adaptability and performance in dynamic manufacturing environments, while maintaining high efficiency despite sudden interruptions. Overall, the proposed approach advances intelligent and adaptive real-time rescheduling in a flexible job shop environment, supporting the Industry 4.0 concept by enhancing the flexibility, efficiency, and performance of intelligent manufacturing systems that can withstand both disturbances and emerging cyber threats
Dynamic flexible job shop scheduling, genetic algorithm, rescheduling, manufacturing systems, optimization, disturbances, cyber-attack
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