SR&ED Case Study: Warehouse Routing Optimization at Scale

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Background

A fulfillment technology company’s warehouse routing system, built on a standard shortest-path solver, worked well for smaller facilities but produced increasingly inefficient pick paths as clients expanded into larger, more complex multi-zone warehouses.

The Challenge

The team needed a routing approach that could compute near-optimal pick paths within a strict time budget for warehouses with thousands of SKUs and dynamic order batches, a scale at which the standard solver’s computation time became impractical.

Technological Uncertainty

It was not known in advance whether any combination of algorithmic approximation and heuristic batching could achieve near-optimal routing within the required computation time at this warehouse scale, or whether the problem’s complexity made real-time optimization infeasible at this size.

Experimental Development

The team systematically tested multiple heuristic and approximation algorithms, order-batching strategies, and zone-partitioning approaches, measuring path efficiency, computation time, and solution quality against the standard solver’s baseline across representative warehouse layouts.

What Failed?

An initial heuristic approach met the computation time budget but produced pick paths meaningfully less efficient than the baseline on the largest warehouse configurations, requiring the team to investigate a hybrid zone-partitioning strategy.

Technological Advancement

The team developed a hybrid algorithm combining zone-based partitioning with a refined heuristic solver, achieving near-optimal routing efficiency within the required computation budget across warehouse sizes the original solver couldn’t handle, generating new technical knowledge about real-time routing optimization at this scale.

Potentially Relevant SR&ED Activities

●   Systematic testing of heuristic and approximation algorithms against computation time and efficiency targets

●   Order-batching and zone-partitioning strategy experiments

●   Path efficiency benchmarking against the standard solver baseline across warehouse configurations

What Would Generally Not Qualify

Applying the finalized routing algorithm to additional warehouses of similar size and layout using the established configuration would be routine deployment and would not itself qualify.

Documentation

Computation time and path efficiency benchmarks across algorithm configurations, technical notes on why the standard solver became impractical at scale, and comparative analysis against the baseline would support this claim.

About The Author

Dale Doering

Dale Doering is the owner of SRED Consultants Inc., helping businesses navigate the complexities of Scientific Research and Experimental Development (SR&ED) claims. With a strong understanding of the technical and interpretive requirements of the SR&ED program, Dale works with companies to identify eligible projects, document technological challenges, and clearly demonstrate the systematic experimentation or analysis undertaken to achieve advancement. His approach focuses on translating complex technical work into well-supported SR&ED claims, helping clients maximize eligible opportunities while maintaining a clear understanding of the program’s requirements.

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Frequently Asked Questions

Why did the original warehouse routing system become impractical at larger scales?

The original system relied on a standard shortest-path solver. While it worked well for smaller facilities, as warehouses expanded to include thousands of SKUs and dynamic order batches, the computation time required by the standard solver grew too large to provide pick paths within an acceptable real-time budget.

The key uncertainty was whether any combination of algorithmic approximation and heuristic order-batching could achieve near-optimal routing within the strict computation time limit at scale, or if real-time optimization was fundamentally infeasible for large, multi-zone facilities.

The team systematically tested multiple heuristic and approximation algorithms, order-batching strategies, and zone-partitioning approaches. They evaluated each approach by benchmarking path efficiency, computation speed, and overall solution quality against the standard solver’s baseline across representative warehouse layouts.

The team developed a hybrid algorithm that combined zone-based partitioning with a refined heuristic solver. This solution delivered near-optimal routing efficiency within the required time budget for large warehouse sizes, generating new technical insights into real-time routing optimization at scale.

Simply applying the finalized, established routing algorithm and configuration to additional warehouses of similar size and layout would be considered routine engineering/deployment and would not qualify as eligible SR&ED work.

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