anyLogistix 3.4.0: Last-mile optimization and new Welcome page

anyLogistix 3.4.0 is here and packed with new capabilities to help you solve one of the most complex and customer-sensitive problems in supply chain logistics: Last-Mile Delivery Optimization. Alongside this new simulation experiment, we are also introducing a fresh, intuitive Welcome page for more straightforward navigation and faster access to what matters most. Let's discover in detail what’s new in this latest version.

Contents:

1. Last-mile optimization
• Detailed inputs
• New preview table
• Experiment results
2. New Welcome page
3. Download anyLogistix 3.4.0

LAST-MILE OPTIMIZATION

The last mile refers to the final leg of the supply chain, when goods are delivered from a distribution center to the end customer. It is often the most expensive, unpredictable, and operationally challenging part of the supply chain. It requires tight synchronization of customer-specific operating hours, fleet limitations, route planning, driver schedules, vehicle types, and demand variability.

The way your last-mile operations are managed directly shapes the customer experience. This final delivery step is where your brand meets the customer, so any delays, missed time windows, or inefficiencies are immediately felt. That is why ensuring predictable, on-time deliveries is not just a logistical goal but a customer promise.

The new last-mile optimization experiment in anyLogistix 3.4.0 is specifically designed to solve these challenges by enabling you to minimize total drive time across all delivery routes and improve service levels. Let’s break down the details of this brand-new experiment.

Detailed inputs: take complete control

To get the most from last-mile optimization, define every element involved in the delivery process to ensure the simulation reflects your actual operations:

• Customers & demand: Build your delivery network around real clients and their individual orders.


• Distribution centers (DCs): Choose the exact facilities from which products are shipped. Have multiple DCs or different rules per site? No problem: everything is configurable.


• Fleets & vehicles: Define the number and types of vehicles available at each DC, including capacity and speed. Set return behavior if you operate an in-house fleet rather than renting. If different types of vehicles are available, the optimization experiment will suggest the most suitable options.


• Inventory & sourcing: Control which DCs can ship what products. Inventory links ensure that only valid product-source combinations are used in the experiment.


• Loading & unloading: Set the processing time required for loading and unloading and define maximum vehicle idle time to ensure efficient transportation usage. In addition, consider gate availability at each location, as limited gates (e.g., 2 gates for 5 vehicles) can result in queuing and increased wait times.


• Locations & routing: Input geo-coordinates for DCs and customers, and define the real-world road network between them. Impose maximum route durations and driver travel-time restrictions for regulation-compliant routing.


• Time windows & work schedules: Respect customer availability and DC operating hours by configuring time windows and working periods. The experiment ensures no deliveries occur outside allowed times.

Some of the detailed inputs for the last-mile optimization experiment (click to enlarge)

These and other standard inputs enable anyLogistix users to produce a high-fidelity simulation that accurately reflects the real-world logistics environment.

New preview table: final orders matter

One of the standout features in the last-mile optimization experiment is an entirely new order preview function. It is particularly important for this type of experiment, where individual final orders play a crucial part and should not be clustered. So, before running the optimization, you can:

• View a detailed list of all customer orders included in the experiment, filtered by a wide range of criteria and date ranges.


• Quickly identify and exclude invalid orders (e.g., those with missing unit conversions or unsupported formats).


• Manually edit the order list to match your planning logic and fit unique business constraints.

Orders preview table in the last-mile optimization experiment (click to enlarge)

This flexibility is advantageous when modeling specialized deliveries. For example, you can isolate and simulate shipments of cold-chain products that require refrigerated trucks.

Each order can also have an expected lead time, meaning that it has a creation date and a deadline by which it must be fulfilled. This is a great customer-centric feature of a new last-mile experiment.

With this level of control for previewing and managing input orders, last-mile optimization aligns with business priorities and operational realities.

Experiment results and their usage across anyLogistix

Once you run the last-mile optimization experiment, you can analyze the results using a customizable dashboard and dedicated output tables. The experiment’s optimal result is the scenario with the minimum total drive time required for all routes and with fulfilled demand.

You can interpret the results in the following sections:

• Milk runs: Here, you will find optimized delivery routes outlining the sequence in which customers should be visited. Each milk run acts as a reusable delivery path that multiple shipments can follow. Explore the table listing all milk runs and visualize them on the map.


• Shipments table: This section provides an overview of all shipments from milk runs, including load times , total travel and idle time, shipment duration, actual volumes delivered, total CO2 emissions, transportation costs, and total revenue.


• Shipment schedule table: In this part, each shipment is broken down by statuses like “created,” “processing,” “loading,” “departure,” and “arrival,” contributing to complete transparency.

Consolidated milk runs and some of the output tables in anyLogistix (click to enlarge)

Once you find optimal results, you can reuse them in other parts of anyLogistix, apply them to your current simulation scenario, or incorporate them into a new one. This flexibility means you are never locked into a single analysis. The results of the last-mile optimization experiment flow seamlessly into the rest of your supply chain planning.

Just like in other simulations, the last-mile optimization experiment allows you to investigate and analyze results in detail, providing comprehensive insights and granular data to support research, decision-making, and performance evaluation.

NEW WELCOME PAGE

The redesigned Welcome page in anyLogistix 3.4.0 is a real productivity booster. It helps you get to work faster, stay informed, and find what you need the moment you open the software. Here is what you will see on the new Welcome page:

• Quick access to all projects: Jump into recent projects with a clean list.


• Filter by role: Whether you are an owner, participant, or viewer, you can quickly filter project views based on your involvement to stay focused on what matters most.


• Project status at a glance: View each project’s owner and current participants without opening it.


• Easy navigation to resources: Access key materials like documentation, training videos, and product news right from the Welcome page.


• Environment settings: Customize the page to display only what you need.

The new Welcome page (click to enlarge)

TRY THE NEW VERSION TODAY!

Download anyLogistix 3.4.0 now and experience the power of last-mile optimization. See the new Welcome page for yourself and boost your productivity. Check out the release notes for more technical information.

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