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Minimal Cost All-Reachability in DAG

Thinking Mode

Summary

  • •Phase 6 / graph/dag/transitive-closure
  • •Reasoning-first competitive programming drill

Problem Description

Given a weighted DAG with n nodes and m edges, choose a set of edges (possibly empty) to add (not given in the input), such that after adding them, every node is reachable from every other node, and the sum of edge weights added is minimized. How to read this problem in plain language: - This is a Phase 6 reasoning drill focused on graph/dag/transitive-closure. - Typical lenses to test first: graph, dag, minimum. - Constraints reminder: 1 ≤ n≤2000, 1 ≤ m≤5000, 1 ≤ w≤106, 1 ≤ q≤105 Mini examples for mental simulation: 1) Boundary example: Describe why this case is tricky. Explain expected behavior and why naive logic may fail. 2) Adversarial example: Adversarial case where naive greedy/local decision looks correct but fails globally. Lite-mode writing target: - Write 1~2 observations that shrink the search space. - Name one final algorithm and state target complexity explicitly. - Validate with at least 2 edge cases and one hand simulation.

Constraints

  • •
    1 ≤ n≤2000, 1 ≤ m≤5000, 1 ≤ w≤106, 1 ≤ q≤105

Analysis

Key Insight

Use this hint to refine your reasoning. This step should reduce search space or formalize correctness. State why this insight changes your algorithm choice.

graphdagminimumreachability
graphdagminimumreachability