How Newton.Vaureal Consulting saves 12% on logistics opex costs with Hexaly
Newton.Vaureal Consulting is a consultancy company specializing in operations management since 1998. Newton has a team of Operations Research specialists to handle all modeling needs that arise in business projects, such as logistics network design optimization. With six network design projects carried out by relying on Hexaly Optimizer last year, Newton optimized €160M of logistics costs overall and obtained 12% savings for its clients on average. In this case, Newton’s team sought to optimize the network design of one of its clients.
Network design problem
Every year, Newton accomplished a number of consulting projects to optimize dense logistics networks for B2B or B2C retailers. The project presented below involves a French retailer of frozen food delivered at home (€70M in revenue). The retailer operates 2 preparation sites to prepare customer orders, and further transports them to 70 distribution sites. Given an expected increase in sales of 15% in the next three years, the goal was to challenge the economic efficiency of the logistics network of this retailer: optimal number and location of distribution (level 1) and preparation sites (level 2).
Input data
- 300,000 customers grouped into 3,700 geographical clusters
- 70 distribution sites + 250 greenfield locations for new sites
- 2 preparation sites + 250 greenfield locations for new sites
- 1 million decision variables
Decisions
Find the optimal number and location of preparation and distribution sites.
Constraints
- Each customer is assigned to a distribution site
- Each distribution site is assigned to a preparation site
- Lower limit on the activity level of each distribution site
- Capacity of preparation sites
- At most one additional preparation site
Objectives
- Minimize transportation costs for downstream flows
- Minimize fixed and variable costs for preparation sites
- Minimize fixed costs for distribution sites
- Minimize costs for incoming transportation to preparation sites
Hexaly’s results
The first optimization level, about the optimal location of distribution sites, addresses 71% of the total logistics costs and is the most challenging part. Newton’s operations research team efficiently modeled and solved this problem using Hexaly Optimizer. They now obtain near-optimal solutions within 3 minutes of running time.
The financial savings were above 8% overall cost-to-serve and 10% on the first logistics level.
Why Hexaly?
According to Renaud Lacour, Senior Modeling Expert, Newton.Vaureal Consulting has chosen to rely on Hexaly as an optimization solver for three main reasons. First, the optimization engine is powerful and able to solve optimally or near-optimally the real-world instances that arise in their projects. Second, Hexaly’s high-level, friendly modeling Python API enables them to quickly build readable and reliable mathematical models close to business problems. Last, the technical support is extremely reactive and helpful in improving the efficiency of their models.
The speed, scalability, and unique nonlinear modeling features of Hexaly have enabled us to tackle a variety of problems that MILP solvers like Gurobi and Cplex couldn’t effectively solve. Hexaly Optimizer’s performance has far exceeded our expectations, especially in areas such as traveling salesman (TSP), vehicle routing (VRP), assignment and matching, and facility location problems. With Hexaly, we successfully optimized the entire supply chain network for our customer Argel, achieving an impressive 12% reduction in OPEX. The thorough and responsive support from Nikolas, Senior Optimization Scientist at Hexaly, has been invaluable in helping us make rapid progress on our projects. We are extremely impressed by Hexaly’s capabilities and the substantial impact it has had on our business.
Please look at our customers‘ webpage to discover more case studies in various industries.
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