.png){kind=icon}
.png){kind=icon}
Return
Simulation–Validated Genetic algorithm scheduling for industrial production systems
.png){kind=icon}
OA
AI
DOI：10.1016/j.cie.2026.111915.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
• Developed a Genetic Algorithm based scheduling framework for configuration-dependent industrial job-shop systems. • Integrated discrete-event simulation as an iterative, feasibility-oriented validation layer for scheduling optimization. • Demonstrated substantial makespan reduction and utilization improvements in an industrial commissioning-stage case study. • Showed how strengthening simulation-based validation enhances the practical credibility of GA-based scheduling results.
Keywords:
Industrial Engineering
Production Scheduling
Genetic Algorithm
Discrete Event Simulation
Simulation-Optimization
Job-Shop
Industry 5.0
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
C
IF:
6.5
Papers:
469
Citations:
0