Optimizing Production Scheduling in Smart Manufacturing Systems Using Hybrid Simulation-Based Multi-Objective Optimization

Abstract is In the era of Industry 4.0, optimizing production operations under dynamic and uncertain environments has become a critical challenge. This study presents a hybrid optimization framework combining discrete-event simulation (DES) and a multi-objective metaheuristic algorithm to enhance production scheduling in smart manufacturing systems. The proposed model addresses trade-offs between throughput, energy consumption, and machine utilization, enabling real-time adaptive decision-making. Experiments were conducted on a flexible job shop scenario, with results indicating significant improvements in operational efficiency compared to conventional heuristics. The research highlights the potential of integrating simulation-based optimization for robust and sustainable production operations.