Optilogic Training Courses teach teams to model, analyze, and optimize supply chains with confidence. Learn Cosmic Frog and DataStar through expert-led, hands-on sessions that deliver faster insights, stronger decisions, and measurable ROI.
Are you looking for greater detail in transportation cost to complement your network designs? Transportation route optimization can provide the insight needed to answer tough questions: Should I consolidate shipments onto multi-stop routes? What should my fleet size be? What empty miles can I save if I incorporate backhauls? Does utilization improve if I adjust my time windows?
Our 2-hour live training session will cover:
Date: January 21, 2026 01:00 PM EST
Explore Optilogic’s on-demand training library, curated to help you learn exactly what you need, when you need it. Access everything at your fingertips and move through each module at your own pace.
This chapter tackles one of the most common hurdles in supply chain modeling: infeasibility. You’ll see how Cosmic Frog flags errors when your model can’t satisfy all its constraints, and more importantly, how to track down the root cause. Starting with the validation report, you’ll learn how to spot critical errors, trace them back through sourcing or transportation policies, and fix the issues step by step.
This session explores the automatic OptiRisk metrics available with each Cosmic Frog scenario. We dig into the components that make up each scenario's risk scores, where to find this reporting within Cosmic Frog outputs, and dashboards available to visualize cost versus risk tradeoffs. We then walk through examples of building and tuning your own risk profiles, and how to respond to risk identified with mitigation scenarios and quantifying impacts of risk events.
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Learn how to navigate the DataStar interface and understand the core concepts behind your data transformation workflows. This overview walks you through the Optilogic platform, including projects, macros, data connections, and how to use Leapfrog AI to build tasks with natural language prompts.
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Ready to take your modeling skills to the next level? Join Leapfrog 102 for a hands-on walk-through of the latest AI-powered use cases—designed to help you explore, edit, and optimize like a pro inside Cosmic Frog.
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This session will give users and introduction to the Hopper engine. Typical Hopper use cases, differences and synergies with other Optilogic engines, and high level solve approach will be covered. The session will also equip users with the base input information needed for models, as well as types of outputs.
This session examines the inputs for an outbound multi stop routing model within Cosmic Frog. Base elements, pickup and delivery constraints, assets, costs and time considerations will be covered.
This session covers Hopper scenarios that consider tradeoffs between reatining current route configurations and customer segmentation vs. relaxation of these rules.
This session covers Hopper scenarios that considers the impact of adjusting various factors when routing outbound shipments. Considerations include business hours, asset types available, and origin locations for the shipments.
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Understand the conceptual elements of simulation modeling, what makes simulation unique as a modeling methodology, and questions that can be addressed with simulation.
Learn the foundational elements of building supply chain simulation models in Cosmic Frog, including Model Elements, Transportation, Sourcing, Production, Inventory, and Demand (Orders).
Step-by-step instruction to be able to confidently run your own simulation model and review outputs.
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In this session, we introduce the fundamentals of NEO optimization models in Cosmic Frog. You'll learn how NEO evaluates millions of possible supply chain configurations to find the least-cost or most profitable way to meet customer demand while respecting every constraint in your network. Instead of manually analyzing trade-offs, NEO automatically determines the optimal combination of suppliers, manufacturing sites, and distribution centers to fulfill orders.
In this episode, we explore two powerful pre-run validation tools in Cosmic Frog: the Model Assistant and the Integrity Checker. Instead of running your entire model, waiting for results, and then diagnosing issues, you can catch data errors in just minutes before hitting "run." The Model Assistant flags missing essential information—like un-geocoded locations or absent production policies—while the Integrity Checker goes deeper, identifying numeric issues, unit of measure mismatches, master data references that don't exist, and data type conflicts.
In this episode, we dive into scenario building in Cosmic Frog—the heart of network optimization testing. Instead of manually reconfiguring your entire model for each "what if" analysis, you create modular scenario items that make specific changes to your data. Want to test closing a facility? Doubling demand for a customer? Removing flow constraints to see optimal behavior? Just build a scenario item, assign it to a scenario, and run. Each scenario can combine multiple items, letting you stack changes and test complex configurations in minutes.
In this episode, we explore how to analyze your optimization results through Cosmic Frog's output tables. Instead of digging through raw solver logs or exporting data to external tools, you can filter, compare, and aggregate results directly within Cosmic Frog. Want to see total cost savings between your baseline and optimized scenarios? Need granular detail on which facilities are shipping to which customers? And it doesn't stop there. You'll see how to use the job logs and error logs to troubleshoot model runs, validate that scenarios completed successfully, and identify where infeasibilities occur. With Cosmic Frog's output tools, analysts can quickly validate results, pinpoint where savings are generated, and confidently present findings to stakeholders.
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Recently, a series of crises including the COVID-19 pandemic and the obstruction of the Suez Canal had a major impact on the global supply chain, resulting in disruptions such as temporary shortages, delayed deliveries, increased uncertainty, and higher costs for goods and services.
Supply chain design technologies like modeling, optimization, and simulation are not new—so why have these once bleeding-edge tools fallen so far behind? Perhaps it’s because the way we’re optimizing supply chains is all wrong. Let’s look at the top five ways traditional supply chain design technology went wrong and how to step into a new era of design for resiliency, delighted customers, and shareholder value with the 100% SaaS-based Optilogic Cosmic Frog supply chain design platform.
PECO uses advanced modeling and cost analysis tools to optimize pallet depot operations, improve network efficiency leading to enhanced customer service and reduced supply chain risks.
Led by MK Capital, New Funding Will Accelerate Further Research and Development of Optilogic’s Cloud-Native SaaS Solution
You understand the importance of looking at a myriad of scenarios as part of the supply chain decision-making process, but some of the terms technology vendors use nowadays can be confusing. Good examples are scenario modeling, what if analysis, and simulation. What’s the difference between each approach?
It’s that time again—an opportunity to look back on the past 12 months and ahead to what the new year will bring. You don’t need to be a supply chain expert to know that we still have challenges ahead.
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Visit our Help Center to explore detailed product guides, troubleshooting tips, and expert insights from the Optilogic community. Whether you’re learning the basics or diving into advanced modeling, you’ll find step-by-step resources to help you get the most out of the Design Intelligence Platform.
Explore all Optilogic resources in one place — from expert-led webinars and thought leadership blogs to customer success stories and product videos.
See how Optilogic combines advanced modeling, risk analysis, and expert support to deliver faster decisions and measurable supply chain results.
