Optimally curtailing supply chain costs is paramount in today’s volatile world. A report released by the International Monetary Fund (IMF) suggested that in 2022, global inflation reached as high as 9.5 percent and is expected to increase in 2023, with food, energy, and transportation costs being the most affected. With this in mind, companies looking to reduce expenditure should better evaluate streamlining their distribution network to coordinate their operations, inventory, and distribution teams.
Volatile price swings at gas pumps require companies to streamline their logistics network
What is Supply Chain Network Optimization?
Supply chain networks consist of various stakeholders ranging from raw material suppliers to destination markets. As the supply chain grows, the scale and complexity of these networks make operating them a challenging problem. Network optimization helps analyze various tradeoffs holistically to identify the following:
- Optimal investment decisions in the location of facilities such as warehouses/hubs
- Optimal operational decisions to determine the routing of goods across the network
Typical Use Cases Pertinent to Supply Chain Network Optimization
- Minimize distance traveled and carbon impact by optimally choosing warehouse and hub locations among potential sites given the required supply and demand needs
- Minimize transport costs and fulfill demand by optimally transporting goods from one facility to another (distribution centers, warehouses, facilities) while fulfilling demand
- Maximize profit and minimize holding costs by aligning production, storage, and demand requirements
Multi-Echelon Supply Chain Optimization
- Maximize network performance by holistically analyzing the complex interdependencies between different supply chain levels (suppliers, intermediaries, factories, distribution centers)
Use Case: Determining Optimal Hub Locations
A furniture company manufactures contemporary sofas in its eight manufacturing facilities. They are looking at reevaluating and optimizing their distribution network. One of their considerations is establishing intermediate hubs and offloading inventory from the manufacturing facilities to improve their delivery process. The goal is to minimize the weighted distance between routes from manufacturing facilities to destination markets, where orders must go through at least one hub before going to brick-and-mortar stores.
A furniture company aims to minimize total weighted shipment distance by determining existing stores to be converted as hubs
Aimpoint Digital Solution
Our team minimized the total weighted mileage in the network by selecting optimal stores as hubs via a mixed-integer linear program (MILP).
Formulating the problem as a MILP provides multiple benefits. MILP models are highly flexible; we do not need to drastically update the model given, for instance, a different set of store locations to analyze. As MILP models are typically written in a generalized format, the model applies to various input scenarios. This allows us to perform scenario analyses on different sets of hubs interactions and shipment flows.
In addition, we can incorporate business requirements easily into MILP models. Those requirements can be written as mathematical constraints which provide restrictions to the decision variables defined. By including all the business requirements necessary to consider, our team was able to effectively model the company’s existing process and generate an optimal solution accordingly.
Having hubs closer to destination locations led to an average decrease in the weighted distance by 10.6% per additional hub. Furthermore, to help users make sense of the results and ensure interpretability, our team automated processes to generate an accompanying visualization. The Tableau dashboard below is based on anonymized data, which visualizes the optimal network for each additional hub.
At Aimpoint Digital, we place special emphasis on ensuring our solutions continue to deliver value for our clients even after our engagement is over. Our solution was packaged in an easy-to-use and interactive form factor and integrated with the client’s existing tech stack. We provided extensive documentation and carried out multiple rounds of user testing. This will allow our clients to easily re-use the solution to re-optimize their network if market conditions change in the future.
Optimize your Supply Chain and Logistics Network with Aimpoint Digital
Contact us through the form below to learn more about how we can help your organization evaluate and maintain efficient supply chain networks in your organization. At Aimpoint Digital, our supply chain experts are ready to deploy optimization-driven solutions and support your organization’s supply chain efforts.