Warm-starting Strategies in Scalarization Methods for Multi-Objective Optimization
Please always quote using this URN: urn:nbn:de:0297-zib-101073
- We explore how warm-starting strategies can be integrated into scalarization-based approaches for multi-objective optimization in (mixed) integer linear programming. Scalarization methods remain widely used classical techniques to compute Pareto-optimal solutions in applied settings. They are favored due to their algorithmic simplicity and broad applicability across continuous and integer programs with an arbitrary number of objectives. While warm-starting has been applied in this context before, a systematic methodology and analysis remain lacking. We address this gap by providing a theoretical characterization of warm-starting within scalarization methods, focusing on the sequencing of subproblems. However, optimizing the order of subproblems to maximize warm-start efficiency may conflict with alternative criteria, such as early identification of infeasible regions. We quantify these trade-offs through an extensive computational study.
| Author: | Stephanie RiedmüllerORCiD, Janina ZittelORCiD, Thorsten KochORCiD |
|---|---|
| Document Type: | ZIB-Report |
| Date of first Publication: | 2025/08/12 |
| Series (Serial Number): | ZIB-Report (25-12) |
| ISSN: | 1438-0064 |

