Inspiration
Shipyard block scheduling is a difficult spatial-temporal optimization problem. A solver must decide where each block should be placed, when it should enter and exit a bay, and how to keep the final schedule feasible under geometry, crane, workload, tardiness, and bay-preference constraints.
We wanted to go beyond simply running the baseline. Our goal was to build a competition-safe solver that always prioritizes feasible output, respects the official checker, and improves objective quality through multiple lightweight search strategies.
What it does
Arcapps: Hybrid Shipyard Solver is a time-guarded heuristic solver for the OGC 2026 shipyard block scheduling problem.
It generates candidate schedules using several strategy families, including fast feasible construction, weighted bay scoring, workload and preference trade-off tuning, ejection-style improvement, and safe fallback logic. Every final candidate is validated with the official utils.check_feasibility() function before being returned.
The solver keeps the official submission interface:
def algorithm(prob_info, timelimit=60):
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