How much can your company save by joint inventory and route optimization?
Posted by dr. Mieke Defraeye on 26/02/2016
Are inventory and transport planning well-aligned in your company? Our experience is that this is often not the case, because keeping inventory and transport planning somewhat separated is considered to be more manageable. Indeed, joint optimization of inventory and transport is much more complex, but it can save your company a lot of money.
3 choices for simultaneous transport and inventory optimization
Simultaneous optimization of inventory and transport planning requires choices about:
- when a customer’s inventory is replenished,
- the order quantities to be delivered,
- And which routes are used to do so.
Ideally, these choices should be made all at the same time, in order to reduce costs while maintaining customer service. This problem is known among researchers as the inventory routing problem (IRP).
When is it relevant
In practice, the inventory routing problem or IRP arises naturally in companies that apply Vendor Managed Inventory, but there are numerous other applications. Consider for instance the replenishment of gas stations based on the tank levels, waste collection based on container fill rate, or the replenishment of department stores from your companies’ central depot.
If we take replenishment of department stores from your companies’ central depot for example, an IRP solution may propose to deliver 1 day earlier if this is beneficial for the transport costs (e.g., there is empty space in a truck that passes the customer that day). Similarly, delivering later is only allowed if sufficient inventory is available at the customer, such that customer service levels are maintained.
As such, it are no longer (only) the orders placed by the customer that drive your route planning, but also the evolution of the customer’s inventories (though in practice, a combination of order-driven and inventory-driven replenishments is common).
Capture cost reductions with holistic optimization
Considering inventory and transport planning jointly implies that you can optimize with the Bigger Picture in mind; this will allow your company to capture considerable cost reductions.
Over the past decades, joint optimization of inventory and transport has been extensively studied by academics worldwide (see Coelho et al. 2013 and Andersson et al. 2010 for literature surveys). Despite this, there remains a clear need for solutions that are capable of handling the numerous practical constraints that arise in real-world IRP problems.
With this in mind, Conundra developed a state-of-the-art IRP-engine that simultaneously optimizes inventory and transport planning. Using a powerful heuristic, we solve inventory routing problems as they exist in practice – large, complex, and practical Inventory Routing Problems or IRPs. Given our focus on practical applicability, many real-world constraints were included in our method:
- Maximal driving times and time windows of drivers are respected
- Time windows at the customer locations are accounted for
- A minimal inter-shift duration for drivers can be imposed
- Vehicle capacity defined on several levels at the same time (weight, volume, or others)
- Maximal inventory (tank capacity or storage space) at customer’s side is respected
- Drop times can be defined for each pickup or delivery
- Trucks are allowed to have an initial quantity of product at the start of the shift
- Suppliers are located at several different locations
- Restrictions on supplier inventory can be imposed
Interested to learn more about the possibilities of a joint inventory and route optimization approach? Interested to join our continuously evolving state-of-the-art research with a test case? We are passionate about optimization and reducing logistic costs, so if you have any questions – let us know.
Conundra qualifies for ROADEF CHALLENGE 2016
At Conundra we are passionate about optimization and passionate about reducing logistics costs. We are realizing significant logistics cost reductions through continuously building bridges between the academic and logistics world. The ROADEF CHALLENGE is an ideal forum for that.
We are benchmarking our IRP-engine academically within the ROADEF challenge, which is an annual competition where academics compete to find the best performing algorithm to a complex and practical case. This year’s topic aims at practical inventory routing, and is based on a case at Air Liquide (gas distribution).
We are delighted to find our IRP engine in 2nd place, in the ranking of the qualification phase of the ROADEF challenge 2016. This shows that our IRP-engine finds excellent solutions for the practical case of the ROADEF challenge, and is promising for solving large, complex, and practical IRPs.
We are passionate about optimization and reducing logistic costs, so if you have any questions – let us know.