EURO-Online login
- New to EURO? Create an account
- I forgot my username and/or my password.
- Help with cookies
(important for IE8 users)
1821. Comparison of Discrete Time and Precedence Based MILP Formulations of Production Scheduling for Furniture Manufacturing
Invited abstract in session TB-49: Lot-sizing with energy aspects, stream Lot Sizing, Lot Scheduling and Production Planning.
Tuesday, 10:30-12:00Room: M1 (building: 101)
Authors (first author is the speaker)
1. | Károly Kalauz
|
Digital Development Center, Széchenyi István University | |
2. | Botond Bertok
|
Széchenyi István University | |
3. | Marton Frits
|
University of Pannonia |
Abstract
Effective production scheduling is essential for optimizing productivity and meeting demand within dynamic production systems. This study conducts a comparative analysis of two modeling techniques, Process Network Synthesis (PNS) and Time-Constrained Process Network Synthesis (TCPNS), in the context of mass production. Both techniques, rooted in P-graphs, excellent in managing complex and flexible recipes.
The precedence-based resource scheduling model employing TCPNS, provides high precision in schedule generation and effective handling of complex changeover times. However, the required computational effort may exceed practical limitations. In contrast, the discrete time process flow model using PNS offers a fast computation through time discretization and a series of combinatorial techniques to reduce the complexity of the mathematical model of the initial problem and sub-problems.
In addition to the comparative analysis, this study examines algorithmic model generation for both precedence and discrete-time formulation, with multiple resolutions in the latter case. This nuanced approach provides an enhanced understanding of the practical applicability and computational efficiency of PNS and TCPNS methodologies, particularly in real-life furniture manufacturing scenarios.
Keywords
- Scheduling
- Combinatorial Optimization
Status: accepted
Back to the list of papers