Start by clarifying requirements and constraints, then outline a greedy algorithm that processes orders and planes in chronological order, assigning cargo to the earliest available plane with sufficient capacity. Discuss how to handle splitting cargo across planes and updating capacities, and analyze time complexity and potential edge cases.
Pro tip: Emphasize that the greedy approach is optimal because assigning cargo to earlier planes preserves later capacity for future orders, and mention that you would validate the solution with unit tests covering edge cases like zero capacity or release times.
Ask about input formats, whether planes can be partially filled, if orders can be rejected, and if there are any constraints on splitting cargo (e.g., minimum chunk size). Confirm that planes have fixed departure times and capacities.
Propose a greedy algorithm: sort planes by departure time, and for each order, iterate through planes departing at or after the order's release time, assigning as much cargo as possible to each plane until the order is fully assigned or no capacity remains.
Use a list of planes with remaining capacities, and for each order, create a mapping of cargo to plane assignments. Update plane capacities after each assignment. Consider using a priority queue or balanced tree for efficient plane lookup if needed.
Discuss time complexity (e.g., O(P log P + O * P) where P is number of planes and O is number of orders) and space complexity. Mention alternative approaches like dynamic programming or max-flow, and justify why greedy is suitable here.
Walk through edge cases: order release time after all departures, insufficient total capacity, exact capacity match, multiple orders competing for same planes. Suggest unit tests and potential optimizations.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.