Split Order Minimization in E-Commerce

Challenge: Online retailers often ship single customer orders from multiple warehouses, leading to increased costs and environmental impact.

Our Solution: A machine-learning assisted algorithm that optimizes product placement across warehouse networks by analyzing historical order patterns, predicting future demand clusters, and optimizing SKU-warehouse assignments.

Results: Significant reduction in split shipments, leading to lower shipping costs, reduced packaging, and enhanced customer satisfaction.

Routing Optimization and Simulation

Challenge: Traditional routing methods struggle with real-world complexities like traffic patterns and periodic deliveries.

Our Solution: In partnership with Attalo GmbH, we’ve developed a dynamic routing framework that integrates realistic driving times, considers periodic deliveries for customers, and optimizes multi-stop delivery sequences.

Results: Our clients experience reduction in fuel and vehicle costs, reduced fleet idle time, and lower carbon emissions.

Large-Scale Simulations of Crowds

Challenge: Major events can overwhelm city transportation systems, creating dangerous bottlenecks and safety risks.

Our Solution: Working with desior GmbH, we’ve created an interactive simulation that models human flow patterns, simulates multiple transportation modes, and accounts for emergency scenarios.

Results: Our system supports event planning and management, infrastructure capacity analysis, and public transportation optimization.