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Models for DIDP.
- Roff 58%
- Python 41.2%
- PDDL 0.8%
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| bin-packing | ||
| configs | ||
| cvrp | ||
| graph-clear | ||
| m-pdtsp | ||
| mdkp | ||
| mosp | ||
| optw | ||
| salbp-1 | ||
| talent-scheduling | ||
| tsptw | ||
| wt | ||
| .gitignore | ||
| LICENSE-Apache | ||
| LICENSE-MIT | ||
| README.md | ||
Models for the DIDP Papers
This repository stores DyPDL, MIP, and CP models used in the following papers.
- Kuroiwa and Beck 2023 CAASDy: Ryo Kuroiwa and J. Christopher Beck. Domain-Independent Dynamic Programming: Generic State Space Search for Combinatorial Optimization. In Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS). 2023. supplement
- Kuroiwa and Beck 2023 Anytime: Ryo Kuroiwa and J. Christopher Beck. Solving Domain-Independent Dynamic Programming Problems with Anytime Heuristic Search. In Proceedings of the 33rd International Conference on Automated Planning and Scheduling (ICAPS). 2023. supplement
- Kuroiwa and Beck 2023 LNBS: Ryo Kuroiwa and J. Christopher Beck. Large Neighborhood Beam Search for Domain-Independent Dynamic Programming. In Proceedings of the 29th International Conference on Principles and Practice of Constraint Programming (CP). 2023.
- Kuroiwa and Beck 2024 Parallel: Ryo Kuroiwa and J. Christopher Beck. Parallel Beam Search Algorithms for Domain-Independent Dynamic Programming. In Proceedings of the 38th Annual AAAI Conference on Artificial Intelligence (AAAI). 2024. supplement
- Journal submission
In addition, PDDL models for some problems and Picat models are provided.
More Models
The discrete-optimization repository maintained by airbus also implement DP models for multiple problems using DIDPPy: https://github.com/airbus/discrete-optimization