Challenge

A prominent glass manufacturer faced significant logistical challenges in optimizing the loading of shipping containers for its glass exports. The glass, cut into varying dimensions of length, breadth, and thickness, had to be packed into containers under strict weight, stacking, and volume constraints. The manufacturer needed a solution to determine the optimal number of containers required to fulfill customer orders with minimal wasted space.

Approach

To address this complex challenge, we employed a dynamic programming algorithm tailored to the manufacturer’s specific requirements. The problem was rigorously formulated as a nonlinear integer optimization model, accommodating numerous constraints related to weight, stacking, and space utilization. Additionally, we integrated heuristics to efficiently navigate the vast search space, enabling us to identify the most effective packing configurations.

Outcome

• Automated Order Processing: An email listener was deployed to automatically extract customer orders and conduct pre-checks before initiating the optimization algorithm.

• Cloud-Based Dynamic Programming Algorithm: The cloud-hosted solution runs seamlessly, generating automated reports that provide the optimal packing configuration for each container.

• Significant Cost Savings: The solution delivered substantial cost savings of approximately $300,000 per annum, reflecting the efficiency gains in container utilization.