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      • Balancing different optimization goals
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      • Designing better routing plans with (just enough) traffic awareness
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Job-oriented guides

This sections helps you solve real-world planning and scheduling problems with Timefold.

They start from a concrete situation: “I have this problem, how do I fix it?” and guide you toward a practical solution by connecting business challenges to optimization concepts, modeling choices, and platform capabilities.

Guides

  • Balancing different optimization goals
    This guide explains how to align multiple, often competing, optimization goals (e.g., coverage, cost, and satisfaction) with your business priorities. It walks through how Timefold’s scoring functions and constraints translate practical trade-offs into measurable metrics, and how you can use our features to balance objectives in real plans.

  • Validating an optimized plan with Explainable AI
    Generating a plan is only half the battle; planners also need to trust the result. This guide shows how Timefold’s explainability features surface real-world metrics and reasoning behind assignments, support human inspection, and help planners understand why a plan looks the way it does.

  • Uncovering inefficiencies in operational planning
    Often a schedule looks fine but still hides bottlenecks or underutilized capacity. This guide helps you identify structural inefficiencies, like resource under- or over-utilization, skill mismatches, geographic imbalances, and other patterns. The guide explains how Timefold helps expose these so you can improve your operations.

  • Responding to disruptions with real-time planning
    Real-world operations change fast. This guide walks through how to handle disruptions such as last-minute requests or unavailable resources by generating actionable recommendations in real time, freezing parts of existing plans that are already in motion, and balancing solution quality with responsiveness.

  • Designing better routing plans with (just enough) traffic awareness
    Adding traffic data to routing is trickier than it sounds. This guide breaks down where and how different types of traffic information matter (from static historic patterns to live feeds), and how to use them effectively (from feasibility checks to optimization) without overwhelming your routing stack.

Goals

Each guide:

  1. Walks through the problem context,

  2. Explains the relevant optimization techniques,

  3. Shows how to apply them effectively with Timefold,

  4. Shows how Timefold is evolving to address these problems even better in the future.

Browse the guides in this section to find the one that best matches your problem and get from challenge to solution faster.

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