Multi-objective optimization for Work-In-Process balancing and throughput maximization in global fab scheduling

This paper presents a multi-objective optimization approach for global fab scheduling, based on a mathematical model that determines production targets, i.e. product quantities to complete in each operation and each period on a scheduling horizon. The multi-objective approach balances product mix variability minimization and throughput maximization using an $\epsilon$-constraint approach. For evaluation purposes, the global fab scheduling model is coupled with a generic multi-method simulation model. Numerical experiments conducted on industrial data illustrate the effectiveness of the approach.