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Main Authors: Heßler, Katrin, Hintsch, Timo, Wienkamp, Lukas
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2410.01445
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author Heßler, Katrin
Hintsch, Timo
Wienkamp, Lukas
author_facet Heßler, Katrin
Hintsch, Timo
Wienkamp, Lukas
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2410_01445
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle A Fast Optimization Approach For A Complex Real-Life 3D Multiple Bin Size Bin Packing Problem
Heßler, Katrin
Hintsch, Timo
Wienkamp, Lukas
Optimization and Control
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.
title A Fast Optimization Approach For A Complex Real-Life 3D Multiple Bin Size Bin Packing Problem
topic Optimization and Control
url https://arxiv.org/abs/2410.01445