The online market is a rapidly growing sector which comprises a significant part of the global market. As stated in the Eurostat report from 2015, the benefits of online trade are enormous, both for the sellers and the buyers. They include lower costs and no geographical limitations on purchases.



Shops have to implement online shopping

Clients are increasingly interested in shopping online. This trend also includes shopping for groceries. Today, all the major supermarket chains offer online shopping. The service allows clients to select the time window for the delivery. It is attractive to customers as they can shop online 24/7, save time or avoid transporting heavy or cumbersome items home.

The Vehicle Routing Problem aims to devise a set of optimal routes from one or multiple depots to multiple clients while considering a series of limitations. The goal is to deliver goods to all clients at minimal route costs and the lowest number of vehicles. Thanks to the universality of the VRP algorithms, many industries may use them. Including the transportation of foodstuffs to customers.


VRP will improve the delivery of groceries

Manual routing for vehicles delivering groceries generates a lot of complexities for the logistics team. Without using optimization algorithms, employees have to schedule and plan delivery routes by hand. Typically it takes place in the morning on the day of the delivery. Workers make sure that all the requirements regarding delivery time will be met, for all the consignments shipped that day.

Unfortunately, the manual method of route planning is rarely optimal.


Examples from the market

The Hong Kong transportation company GoGoVan is a good example of illustrating a usage of algorithms. Scheduling a non-optimal route for 100 points took one person around 1 hour. A higher number of points increased that time. If a company grows and takes in a higher number of orders, manual routing is almost impossible without using algorithms. Additionally, it may result in many mistakes.

The increasing popularity of shopping for groceries via mobile applications or online platforms has been a challenge for companies delivering food. A higher number of orders, translating to a higher number of deliveries, has pushed companies to search for solutions streamlining this difficult process. The answer is route optimization.

Companies delivering foodstuffs to clients face a number of challenges. The main complexity stems from the fact that foodstuffs spoil easily. This is why they require more investment in the infrastructure of storage and delivery, such as specialist commercial vehicles equipped with cold stores. Perishable goods, delivered in cold temperatures, arrive fresh and meet high quality standards.

However, such investments require also higher capital. Hence, planning transportation based on the VRP is beneficial. Why? Due to reduced transportation costs and guaranteed client satisfaction from timely deliveries that meet time windows. In order to limit the problem of inefficient delivery, companies ought to consider key factors such as delivery time and cost. These can be challenging. Particularly in the case of deliveries that should be made on the day when the order was placed.


Easy and quick online sale


The retail industry increasingly focuses on the client. Stores are introducing new functions and services to attract more customers. For instance, a chain of American stores „Walmart” is researching and developing ways of making shopping easier for their clients, who are often busy and have no time to get groceries.

In June 2016, Walmart launched a pilot program aimed at testing foodstuffs deliveries to clients via companies such as Uber and Lyft. The program was also aimed at tackling the problem of the last mile.

Here is how Walmart described the course of the process:

While placing an order online, a client selects the delivery window according to his or her preferences. Next, Walmart’s employees carefully complete the order. After that, a team responsible for deliveries books a driver at Uber or Lyft. It delivers the order directly to the client’s in a way that is the most convenient and hassle-free.



Another American retailer offering grocery delivery services is „Woodman’s Markets” from Wisconsin. It enables order delivery to a customer’s house via its website. Currently, the orders are completed via its own vehicles and Woodman’s drivers. Because demand varies from day-to-day, Woodman’s has to manage the size of its fleet well.

If Woodman’s invested in a large fleet based on high, maximal demand, it would incur high investment costs and in the periods of low demand, excess commercial vehicles would generate extra costs. If Woodman’s invested in commercial vehicles based on lower demand, there might be situations when too few vehicles would offer too little capacity to deliver all the placed orders. An insufficient size of the vehicle fleet might then result in losing customers’ business.

Woodman’s can approach the problem as Walmart did. Mainly, it can use outsourced ride share companies such as Uber in order to satisfy excess demand. The following case study considers a hypothetical implementation of this strategy.


Let’s analyze the problem

Woodman’s has to arrive at a set of routes that come at a minimal cost and provide that the driver visits each client once in the specified time window. Each route starts and ends in the depot (Woodman’s grocery store).

Company’s vehicles or an extrenal outsourced company may covere routes. Each customer has a specified need expressed in the number of standard boxes. Vehicles have capacity constraints that may vary between store-owned vehicles and outsourced vehicles. One may assume that the size of the fleet may be adjust to meet an average demand for delivery services. Vehicles of outsourced companies are meeting excess demand that store-owned fleet cannot meet.

To sum up, the discussed problem with foodstuffs delivery can be modeled as the problem of time windows and vehicle capacity. Store vehicles and vehicles of outsourced companies performing transportation services may have different capacities. It is a heterogenous problem of routing vehicles with time windows. The aim of the problem is to minimize route costs. The constraints necessitate optimal routes which will consider vehicle capacity, time windows and the requirement that clients’ orders must be delivered by a single vehicle.

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