4421. HCPGA-II: Upper Bound Heuristics and Constraint Handling Techniques for Hybrid JSSP Optimization
Invited abstract in session TF-43: Metaheuristics for Scheduling and Timetabling, stream Metaheuristics.
Tuesday, 16:15-17:45Room: JUR – Seminar-Raum 63
Authors (first author is the speaker)
| 1. | Chiara Camilla Rambaldi Migliore
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| Department of Information Engineering and Computer Science, University of Trento | |
| 2. | Giovanni Iacca
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| University of Trento | |
| 3. | Marco Roveri
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| University of Trento |
Abstract
The Job Shop Scheduling Problem (JSSP) is an NP-hard problem critical to Industry 4.0, yet a gap persists between academic research and real-world deployment. Lorenzi et al. (GECCO 2025) proposed hcpga, a hybrid approach combining a CP solver (cp-sat) for initial feasible solutions with a Genetic Algorithm for refinement. We extend this work by evaluating industry-like instances, introducing heuristic upper bounds as CP constraints to accelerate initial solution search, and analyzing constraint handling techniques in the GA compared to the repair mechanism first introduced in hcpga.
Keywords
- Constraint Programming
- Genetic Algorithms
- Combinatorial Optimization
Status: accepted
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