Logistics projects.

Demand Variability

Significant fluctuations in demand for container shipments, leading to inefficiencies in resource allocation.

Complex Route Management

Managing over 5,000 shipping routes with varying volumes and demand patterns.

Forecast Accuracy

Need for precise demand forecasts to improve planning and operational efficiency.

Advanced Demand Forecasting Pipeline

Implemented Giotto’s state-of-the-art meta-ensemble stacking and topological time series technologies to predict demand across multiple levels of aggregation.

Data Integration

Incorporated seasonality data, client volumes, macroeconomic indicators, and weather data to enhance forecast accuracy.

Detailed Multi-Level Forecasts

Provided forecasts from depot to depot, port to port, country to country, ensuring comprehensive coverage.

Improved Forecast Accuracy

Achieved accurate demand predictions for over 5’000 route combinations, outperforming internal predictions.

Enhanced Operational Efficiency

Optimized resource allocation and reduced inefficiencies in shipping operations.

Better Planning and Execution

Enabled proactive planning and improved response times, leading to smoother operations.

Complex Scheduling

Coordinating schedules for vessels, trains, and trucks across a vast network with diverse constraints.

Inefficient Resource Allocation

Difficulty in optimizing resource utilization, leading to increased costs and downtime.

Environmental and Regulatory Compliance

Ensuring compliance with environmental regulations and minimizing carbon emissions.

AI-Driven Schedule Optimization

Implemented Giotto’s sophisticated mixed integer programming strategies for optimal scheduling across intermodal transport modes.

Real-Time KPI Optimization

Used AI to balance key performance indicators (KPIs) like journey time, downtime, fuel consumption, and total costs.

Customizable Constraints

Allowed clients to set the relative importance of each KPI, tailoring the solution to specific network constraints and requirements.

Enhanced Operational Efficiency

Produced globally optimal schedules, reducing downtime by 40% and improving resource utilization.

Cost Reduction

Lowered operational costs by 25% through better planning and reduced fuel consumption.

Improved Compliance

Ensured adherence to environmental regulations and minimized carbon emissions by 20%.

Intermodal Coordination

Managing the interfaces between shipping, rail, air freight, and road logistics to ensure seamless transitions.

Operational Inefficiencies

High friction at intermodal boundaries causing delays and increased costs.

Complex Constraint Management

Handling the complexity of global intermodal logistics networks with diverse constraints.

Intermodal Flow Optimizer

Implemented an intermodal optimizer to create efficient routing plans that utilize multiple transport modes.

Custom Constraint Solving Tools

Used sophisticated algorithms to address and solve complex logistics constraints.

Detailed KPI Optimization

Generated optimized schedules by aligning millions of local transshipment decisions with global KPIs.

Improved Synchronization

Achieved greater network-wide synchronicity, reducing delays by 30% and improving service delivery.

Cost Efficiency

Lowered operational costs by 20% by minimizing friction at intermodal interfaces.

Enhanced Planning

Provided optimal schedules that balanced vehicle location, port status, demand profiles, and live customer constraints, improving overall planning accuracy by 25%.