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Refactor to use native interfaces in OptimalBranching.jl - #13
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…acking. - Introduce `set_debug_level!` for configurable debug options. - Update functions to include `SearchStatistics` for better performance analysis.
…sult` structure. - Include `twosat.jl` in the Boolean inference module. - Refactor branching functions to return `BranchResult` for improved clarity and performance. - Update debug logging to utilize the new `@dbg` macro for better control over logging levels.
…return values in branching functions.
- Rename `vec2tensor` to `vec_to_tensor` and `lluint2vec` to `longlonguint_to_vec` for better readability. - Update corresponding function calls and tests to reflect the new names. - Improve comments for better understanding of the code logic.
…function. - Add detailed debug logging for branching attempts, including propagated variables and remaining constraints. - Refactor `deduction_reduce` to use `append!` for modifying the reducing queue. - Optimize `subhg` function to improve performance by using a set for decided vertices and reducing iterations.
- Replace `region_cache.jl` with direct region management in `problems.jl`. - Update variable and tensor ID handling to use `Int` instead of custom structs. - Enhance debug logging in various functions for better traceability. - Refactor function signatures and internal logic for consistency and clarity.
… efficiency and clarity.
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October 18, 2025 16:17
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October 20, 2025 14:07
OptimalBranching.jl OptimalBranching.jl
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Refactor to use native interfaces in `OptimalBranching.jl`
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Performance after refactoring
Computation is efficient when the region includes only two tensors (as below); and, performance degrades as the region size increases.