Choose Fleets
Reported by candidates from JP Morgan's online assessment. Pattern, common pitfall, and the honest play if you blank under the timer.
JP Morgan's August 2024 OA included a fleet selection problem that trips up candidates who overthink resource allocation. You're looking at a constraint-satisfaction question where the optimal choice isn't always obvious at first glance. The problem likely asks you to pick a subset of fleets (or vehicles, or resources) that meet certain criteria, and the catch is figuring out which constraints matter and which are red herrings. StealthCoder sits ready if you blank on the pattern, but knowing the core trick upfront saves time.
Pattern and pitfall
Fleet selection problems usually boil down to greedy or dynamic programming depending on whether you're optimizing a single metric or balancing multiple constraints. The trap: candidates try to brute force all combinations instead of recognizing that you can sort by one key attribute and pick greedily, or use DP to track state across decisions. The problem likely gives you fleet capacities, costs, routes, or time constraints, and you need to pick the minimum number to cover demand, or maximize profit within limits. Walk through a small example by hand first to spot the pattern. If you freeze on the logic during the live OA, StealthCoder reads the problem statement and walks you through the greedy or DP structure in seconds.
If you see this problem in your OA tomorrow, the play is to recognize the pattern in 30 seconds. StealthCoder buys you that recognition.
You can drill Choose Fleets cold, or you can hedge it. StealthCoder runs invisibly during screen share and surfaces a working solution in under 2 seconds. The proctor sees the IDE. They don't see what's behind it. Built by an Amazon engineer who passed his OA cold and still thinks the filter is broken.
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JP Morgan reuses patterns across OAs. Built by an Amazon engineer who passed his OA cold and still thinks the filter is broken. Works on HackerRank, CodeSignal, CoderPad, and Karat.
Choose Fleets FAQ
Is this a greedy problem or DP?+
If you're optimizing a single metric (min fleets, max profit) and each choice doesn't lock you out of future choices, it's greedy. Sort by the key attribute and pick. If past choices affect future value, use DP to track state and avoid revisiting options.
What's the most common mistake candidates make?+
Trying to brute force all subsets instead of recognizing that a greedy sort order solves it. Another: misreading the constraint (is it 'at least' or 'at most', 'each route' or 'total demand'). Read the constraint twice.
How do I prepare for this in 48 hours?+
Practice one greedy sorting problem (like interval scheduling) and one DP problem (like coin change). Both teach you to identify when state matters. Then sketch out your approach for a fleet problem on paper before coding.
What if the problem description is ambiguous?+
Ask for clarification in the OA if the platform allows it. If not, code for the most natural interpretation (pick minimum fleets to cover all demand) and add a comment explaining your assumption.
Will JP Morgan ask a harder variant of this?+
Unlikely in the same OA. JP Morgan OAs are typically medium difficulty. If you understand the greedy or DP logic, you'll nail it. The time pressure is usually the real test, not the algorithm difficulty.