Case Study: Leading Retailer reduces transportation costs with Mu Sigma route optimization

Reduced transportation costs for a convenience retailer

Leading Retailer, a major U.S. convenience retailer with more than 8,000 stores, was facing transportation costs in one of its largest markets that were higher than the national average. Working through outsourced 4PLs, the company needed a scalable way to optimize DC-to-store transportation routes and improve logistics performance. Mu Sigma was engaged to help with route optimization for its distribution network.

Mu Sigma developed a route optimization tool using a genetic algorithm augmented with heuristics to design better routes, improve load planning, and reduce miles traveled while respecting operational constraints. The solution helped cut transportation costs by 30% overall, reduced miles traveled by 28% and trucks used by 12% in the pilot, and enabled route audits for any DC within three weeks. Following the successful Florida pilot, the solution was prepared for rollout across the retailer’s DC network.