A Fast Optimization Approach For A Complex Real-Life 3D Multiple Bin Size Bin Packing Problem

Katrin Heßler; Timo Hintsch; Lukas Wienkamp

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arXiv · 2410.01445

A Fast Optimization Approach For A Complex Real-Life 3D Multiple Bin Size Bin Packing Problem

Katrin Heßler·Timo Hintsch·Lukas Wienkamp

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Abstract

We investigate a real-life air cargo loading problem which is a variant of the three-dimensional Variable Size Bin Packing Problem with special bin forms of cuboid and non-cuboid unit load devices (ULDs). Packing is constrained by additional practical restrictions, such as load stability, (non-)stackable items, and weight distribution constraints. To solve the problem, we present an insertion heuristic embedded into a Randomized Greedy Search. The solution space is limited by only considering certain candidate points (so-called extreme points), which are promising positions to load an item. We extend the concept of extreme points proposed in the literature and allow moving extreme points for non-cuboid ULDs. A special sorting of the items is suggested, which combines a layered structure and free packing. Moreover, we propose dividing the space of each ULD into smaller cells to accelerate the collision, non-floating, and stackability check while loading items. In a computational study, we analyze individual algorithm components and show the effectiveness of our method on adapted real-life instances from the literature.

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Katrin Heßler, Timo Hintsch, Lukas Wienkamp. 2024-10-02. A Fast Optimization Approach For A Complex Real-Life 3D Multiple Bin Size Bin Packing Problem. https://arxiv.org/abs/2410.01445

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