A Grasp Algorithm for the Container Loading Problem With Multi-Drop Constraints

Martínez, David Álvarez; Álvarez-Valdés, Ramón; Parreño, Francisco

doi:10.1590/0101-7438.2015.035.01.0001

Cited by 24 publications

(14 citation statements)

References 48 publications

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“…After each piece is replaced with a box, an algorithm is used to pack the boxes within the cuboid. The chosen algorithm in this study was the one proposed by Martínez et al (2015) due to the flexibility and efficiency of its solutions.…”

Section: Initialization Methodsmentioning

confidence: 99%

“…The algorithm proposed by Martínez et al (2015) had a constructive phase and an improvement phase. Throughout the first (constructive) phase, the algorithm returned at least one packing pattern, mainly composed of the boxes' positions and some feasibility indicators.…”

Section: Initialization Methodsmentioning

confidence: 99%

“…It is worth noting that the algorithm proposed by Martínez et al (2015) was developed for the container loading problem, in which the container's dimensions are known, i.e., the container's dimensions are parameters of the algorithm. Therefore, an initial container size was supposed, and it was iteratively increased until the feasibility indicators stated that all boxes were successfully packed within the container (cuboid).…”

Section: Initialization Methodsmentioning

confidence: 99%

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A hybrid approach of simulation and metaheuristic for the polyhedra packing problem

Pantoja-Benavides¹,

Álvarez‐Martínez²

2022

10.5267/j.ijiec

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This document presents a simulation-based method for the polyhedra packing problem (PPP). This problem refers to packing a set of irregular polyhedra (convex and concave) into a cuboid with the objective of minimizing the cuboid’s volume, considering non-overlapping and containment constraints. The PPP has applications in additive manufacturing and packing situations where volume is at a premium. The proposed approach uses Unity® as the simulation environment and considers nine intensification and two diversification movements. The intensification movements induce the items within the cuboid to form packing patterns allowing the cuboid to decrease its size with the help of gravity-like accelerations. On the other hand, the diversification movements are classic transition operators such as removal and filling of pieces and enlargement of the container, which allow searching on different solution neighborhoods. All simulated movements were hybridized with a probabilistic tabu search. The proposed methodology (with and without the hybridization) was compared by benchmarking with all previous works solving the PPP with irregular items. Results show that satisfactory solutions were reached in a short time; even a few published results were improved.

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Section: Initialization Methodsmentioning

confidence: 99%

Section: Initialization Methodsmentioning

confidence: 99%

Section: Initialization Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A hybrid approach of simulation and metaheuristic for the polyhedra packing problem

Pantoja-Benavides¹,

Álvarez‐Martínez²

2022

10.5267/j.ijiec

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show abstract

“…The items are thus grouped by destination, but also arranged in the container according to the delivery sequence to avoid unnecessary unloading and reloading operations [ 21 , 22 ]. Two characteristics of the items were defined and used to constrain the positions of the items within the multi-drop framework: visibility and touchable [ 23 ]. They guarantee a form of accessibility of the items during deliveries.…”

Section: Literature Reviewmentioning

confidence: 99%

Pervasive Digital Twin for PI-Containers: A New Packing Problem

Charpentier

Chaxel

Krommenacker

et al. 2021

Sensors

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The idea defended in this paper consists in finding, at any time and everywhere, the arrangement of containers within a composite container. The digital image of the real arrangement obtained defines its digital twin. This image evolves at the same time as its real twin. It can be used throughout the logistics chain during loading/unloading phases in hubs, to check the completeness of a load, to find the particular position of a container, etc. This digital twin is obtained through the collection of neighborhood information from the sensor nodes embedded on each container. This embedded solution allows accessibility to this information everywhere. This proximity information and the instrumentation of the containers define new types of constraints and a new version of a packing problem. We propose here a model integrating them. This model is implemented and tested on different test cases, and numerical results are provided. These show that, under certain conditions that will be presented, it is possible to obtain the digital twin of the real arrangement.

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“…For a variant of this problem, the so-called container loading problem, which differs in the fact that, in general, constraints limiting the possibilities of layers overlapping are not explicit, we refer to [20][21][22][23][24][25][26][27][28][29]. (ILP strategy [23], GRASP method [20,24,25], heuristic way [27], heuristic-genetic algorithm [28], heuristics and MILP method [26], layer-based greedy strategy [21]).…”

Section: Introductionmentioning

confidence: 99%

Solving a Real-Life Distributor’s Pallet Loading Problem

Dell’Amico

Magnani

2021

MCA

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We consider the distributor’s pallet loading problem where a set of different boxes are packed on the smallest number of pallets by satisfying a given set of constraints. In particular, we refer to a real-life environment where each pallet is loaded with a set of layers made of boxes, and both a stability constraint and a compression constraint must be respected. The stability requirement imposes the following: (a) to load at level k+1 a layer with total area (i.e., the sum of the bottom faces’ area of the boxes present in the layer) not exceeding α times the area of the layer of level k (where α≥1), and (b) to limit with a given threshold the difference between the highest and the lowest box of a layer. The compression constraint defines the maximum weight that each layer k can sustain; hence, the total weight of the layers loaded over k must not exceed that value. Some stability and compression constraints are considered in other works, but to our knowledge, none are defined as faced in a real-life problem. We present a matheuristic approach which works in two phases. In the first, a number of layers are defined using classical 2D bin packing algorithms, applied to a smart selection of boxes. In the second phase, the layers are packed on the minimum number of pallets by means of a specialized MILP model solved with Gurobi. Computational experiments on real-life instances are used to assess the effectiveness of the algorithm.

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A Grasp Algorithm for the Container Loading Problem With Multi-Drop Constraints

Cited by 24 publications

References 48 publications

A hybrid approach of simulation and metaheuristic for the polyhedra packing problem

A hybrid approach of simulation and metaheuristic for the polyhedra packing problem

Pervasive Digital Twin for PI-Containers: A New Packing Problem

Solving a Real-Life Distributor’s Pallet Loading Problem

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