The Challenge
A major logistics provider in North America, with an extensive linehaul distribution network and hundreds of end-of-line stations, faced mounting operational costs—reaching $700 million annually. The company wanted to assess whether reconfiguring their distribution centers (DCs), routes, and transportation modes could result in measurable cost efficiencies without compromising service levels or delivery timelines.
The challenge was to intelligently evaluate millions of possible network combinations involving DC locations, equipment utilization, and transportation modes, while still accounting for demand variability and service constraints.
The Solution
Evalueserve partnered with the client to develop a mathematical optimization model, leveraging Mixed-Integer Programming (MIP) to minimize the total network cost. This included fixed facility costs, transportation costs (both loaded and empty miles), and operational constraints such as service level targets and equipment balancing.
The solution involved:
- Analyzing historical demand patterns across origin-destination pairs
- Building a flexible modeling framework with a dynamic front-end tool for scenario comparisons
- Incorporating road and rail transport modes
Running simulations for various business scenarios including peak demand periods, DC closures, and varying service levels
Business Impact
Through this robust optimization effort, the client achieved:
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Annual cost savings exceeding $100 million
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A revised network design with optimal DC locations, capacity allocation, and routing recommendations
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An intuitive dashboard that allowed business users to compare side-by-side scenarios for informed decision-making
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Improved service times and equipment utilization across the board
The optimization model did not just solve for today’s network—but created a future-proof blueprint capable of adapting to market fluctuations, demand shifts, and infrastructure changes.
Overview & Impact
A top logistics provider partnered with Evalueserve to optimize its $700M+ linehaul network. Using Mixed-Integer Programming, the team redesigned the distribution network, unlocking massive cost savings without compromising service.
