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Design elevator scheduling for small building

Last updated: Jun 27, 2026

Quick Overview

Design elevator scheduling for small building evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

  • medium
  • PayPal
  • System Design
  • Data Scientist

Design elevator scheduling for small building

Company: PayPal

Role: Data Scientist

Category: System Design

Difficulty: medium

Interview Round: Onsite

##### Question Design the control policy for a single elevator serving a small building: 3 floors plus 1 basement (stops at B, 1, 2, 3). The goal is to decide, at each moment, where the elevator should go next so as to minimize passenger waiting and in-car travel time. Cover the following: 1. **Objectives.** Define what you are optimizing for (e.g., minimize average wait time and average system time, bound tail latency, avoid starvation, handle peak traffic) and the trade-offs between them. 2. **Constraints.** Specify the physical and operational constraints (car capacity / weight limit, floor-to-floor travel time, door open/close and dwell times, safety interlocks, stops only at B/1/2/3). 3. **Inputs and state.** Identify the inputs the controller observes (hall up/down calls with direction, in-cab destination calls, current position and direction, door state, load estimate, timers) and the internal state it maintains. 4. **Scheduling strategy.** Propose how the elevator decides its next stop. Discuss directional collective control (SCAN/LOOK), basement / peak-traffic priority, anti-starvation, capacity-aware boarding, and optional destination grouping. 5. **Data structures.** Describe the supporting data structures and the control state machine. 6. **Simulation plan.** Outline how you would compare candidate policies under varying arrival distributions (off-peak, up-peak, down-peak, bursty), which metrics to track, and how to validate the results.

Quick Answer: Design elevator scheduling for small building evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

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|Home/System Design/PayPal

Design elevator scheduling for small building

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Jul 31, 2025, 12:00 AM
mediumData ScientistOnsiteSystem Design
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Design elevator scheduling for small building

Design the control policy for a single elevator serving a small building: 3 floors plus 1 basement (stops at B, 1, 2, 3). The goal is to decide, at each moment, where the elevator should go next so as to minimize passenger waiting and in-car travel time. Cover the following:

  1. Objectives. Define what you are optimizing for (e.g., minimize average wait time and average system time, bound tail latency, avoid starvation, handle peak traffic) and the trade-offs between them.
  2. Constraints. Specify the physical and operational constraints (car capacity / weight limit, floor-to-floor travel time, door open/close and dwell times, safety interlocks, stops only at B/1/2/3).
  3. Inputs and state. Identify the inputs the controller observes (hall up/down calls with direction, in-cab destination calls, current position and direction, door state, load estimate, timers) and the internal state it maintains.
  4. Scheduling strategy. Propose how the elevator decides its next stop. Discuss directional collective control (SCAN/LOOK), basement / peak-traffic priority, anti-starvation, capacity-aware boarding, and optional destination grouping.
  5. Data structures. Describe the supporting data structures and the control state machine.
  6. Simulation plan. Outline how you would compare candidate policies under varying arrival distributions (off-peak, up-peak, down-peak, bursty), which metrics to track, and how to validate the results.

Constraints & Assumptions

  • Preserve the scope, facts, inputs, and requested outputs from the prompt above.
  • If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
  • Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.

Clarifying Questions to Ask

  • Clarify users, core use cases, read/write patterns, scale, latency, availability, and data retention.
  • State explicit assumptions before making sizing or architecture decisions.
  • Prioritize the functional path first, then address reliability, security, observability, and rollout.

What a Strong Answer Covers

  • A scoped requirements summary with concrete non-goals and success metrics.
  • API, data model, architecture, consistency, capacity, and operations.
  • Reasoned trade-offs among simple and scalable designs, including bottlenecks and failure modes.
  • A validation, monitoring, migration, and launch plan appropriate for the risk level.

Follow-up Questions

  • What breaks first at 10x traffic or data volume?
  • How would you degrade gracefully during dependency failures?
  • What metrics and alerts would prove the design is healthy after launch?

Submit Your Answer to Earn 20XP

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