What data do I need for successful optimization?

To effectively optimize your loading plan, three types of data are necessary:

• Order Forms: with the requested product quantities.
• Product Packaging Characteristics: weight, dimensions, stackability, etc.
• Supports and Containers: a list of supports such as boxes or pallets, and available containers or AKE and ULDs, along with their characteristics.

This data will enable to create an optimal loading plan, maximizing space utilization while ensuring the safety and stability of the transported goods.

What types of problems are addressed?

Packing optimization software can meet various objectives:

• 2D/3D Palletization Optimization involves building pallets ensuring their stability, stackability, and homogeneity, taking into account their positioning in the vehicle to maximize filling rates and automate the palletizing process.
• Bin Packing Problem (BPP) Optimization aims to reduce the number of resources used, namely the number of containers, trucks, AKEs, or ULDs needed to maximize filling rates and thus reduce empty spaces. It allows combining pallets and bulky/voluminous/heterogeneous products, ensuring an evenly distributed weight for optimal Tetris loading.
• Linear Meter Optimization aims to minimize floor occupation and pool resources by planning a “Last In, First Out” sequencing to facilitate loading and unloading of the vehicle in cases of multiple delivery points (e.g., multi-client delivery).

By integrating these complex constraints, loading optimization software offers tailored solutions to maximize fleet capacities, ensure faster deliveries, and achieve significant cost savings.

Benefits of Packing Optimization

Software solutions for truck loading and container loading offer numerous benefits, starting with the automation of the loading plan construction. The tool relieves the time-consuming and tedious task of building the plan, making it more reliable (fewer mistakes), and reducing leftovers at docks, thanks to 2D/3D visualizations of the loading plan.

But above all, packing optimization rationalizes resource use, thanks to the optimization of loading space and fair load distribution, thus leading to reduced transportation costs. In a similar use case, the benefits were both economic and ecological, with better filling rates (+15% per truck) and thus fewer empty trucks traveling, thereby reducing the environmental footprint of the routes.

By integrating these advanced packing optimization strategies, logistics and planning professionals can not only improve the productivity and efficiency of their teams but also significantly contribute to decarbonizing deliveries for greener logistics.