AI & Technical question

How would you design a system that allocates package delivery orders to drivers and maximizes fufillment during busy and non busy hours

Practice this question out loud. An AI interviewer asks it, follows up like a real interviewer would, and scores your answer. Type or speak.

What this question tests

System and algorithm design for a real-time optimization and fairness problem in logistics.

Clarify the objective: maximize fulfilled deliveries per hour while keeping driver utilization and cost efficient across peak and non-peak.
Define inputs: order locations and deadlines, driver locations and capacity, and real-time traffic.
Propose the core approach: a batching and matching algorithm that clusters nearby orders per driver route.
Handle busy versus non-busy differently: during peaks, prioritize throughput via tighter batching; during lulls, prioritize driver utilization and fairness.
Add guardrails: SLA and deadline adherence, and driver workload fairness so idle time isn't skewed.
Define success as on-time delivery rate and average orders per driver-hour across both regimes.

Distinguishes the busy versus non-busy regime explicitly, since the optimal objective function actually changes.
Names a concrete algorithmic family, assignment and matching with batching, instead of a vague 'use AI.'
Adds a fairness guardrail, driver idle time and order distribution, a real operational concern beyond pure efficiency.

Proposing a single static rule that ignores how the optimal strategy differs between peak and off-peak.
Ignoring driver-side fairness and pay implications, which real logistics systems must consider.

Chapters of the AI PM course that teach what this question tests.