Add hyper-tuned capacity pathing for assignable via pipeline - first working solver for global planning with assignable vias against viagrid test #293
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…rove obstacle and used node filtering logic and update visualization steps fix pathfinding to exclude nodes containing obstacles unless they contain targets and exclude already used nodes early remove large cost penalties for reused nodes in cost and heuristic calculations to simplify logic enhance visualization by adding green lines for solved subpaths and update stroke colors and step numbering for clarity
seveibar
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| { | ||
| onSolved: (cms) => { | ||
| const winningSolver = cms.initialPathingHyperSolver?.winningSolver | ||
| if (winningSolver) { | ||
| // cms.initialPathingSolver = winningSolver |
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The hyper-parameter step constructs initialPathingHyperSolver but the onSolved handler never assigns its winningSolver to initialPathingSolver. As a result initialPathingSolver stays undefined and the following pathingOptimizer step falls back to a default greedy solver instead of using the tuned directive solver. The regression test added in this commit also asserts that winningSolver equals initialPathingSolver, so leaving this assignment commented out causes the test (and the pipeline’s downstream visualization) to fail and the hyper search has no effect.
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Summary
Testing
https://chatgpt.com/codex/tasks/task_b_6901bf9173f4832e858ecc6df1169a24