This one took me a minute to even figure out what they wanted.
Start by clarifying requirements and constraints (e.g., real-time vs. batch, optimization goals, elevator state). Then propose a dispatch algorithm (e.g., greedy with cost function) and outline data structures for elevators and requests. Finally, discuss trade-offs and potential improvements like look-ahead or machine learning.
Pro tip: Emphasize that the algorithm must be efficient for online requests and scalable to many elevators; consider using a priority queue or min-heap for elevator selection. Also, mention that you would test with edge cases like simultaneous requests and full elevators.
Ask about input format, elevator capabilities (capacity, speed), optimization criteria (wait time, energy), and whether requests are processed online or in batch.
Model each elevator's state (current floor, direction, load, destination queue) and define a cost function to estimate the time or distance to serve a request.
Choose an algorithm (e.g., greedy, round-robin, or more sophisticated like LOOK) to assign each request to the elevator with minimal cost, ensuring real-time efficiency.
Outline data structures (e.g., priority queues for requests and elevator queues) and discuss time/space complexity, potential optimizations, and handling of dynamic updates.
Compare your approach with alternatives (e.g., centralized vs. decentralized, simple vs. predictive) and mention possible improvements like learning-based dispatch or handling of emergencies.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.