MIP-based constructive heuristics for the three-dimensional Bin Packing Problem with transportation constraints

Paquay, Célia; Limbourg, Sabine; Schyns, Michaël; Oliveira, José Fernando

doi:10.1080/00207543.2017.1355577

Cited by 36 publications

(14 citation statements)

References 19 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In two recent works [21] and [23] the authors succeed in providing a complete formulation of the problem and efficient resolution methods for industrial applications. More in detail, [23] defines a mixed integer programming problem able to find a solution to the three-dimensional Multiple Bin Size Bin Packing Problem with bins of different shapes to fit inside an aircraft. For the resolution of this specific problem, three heuristics are adopted, i.e., Relax-and-Fix, Insert-and-Fix and Fractional Relax-and-Fix.…”

Section: A Related Work On 3d-bppmentioning

confidence: 99%

“…In particular, differently from [22] and [29], the proposed algorithm allows the definition of multiple bins of homogeneous and heterogeneous items. With respect to [23] and [25], our algorithm takes into account also compatibility constraints among items, e.g., food is not packed with chemical products, and fragility constraints. Moreover, similarly to [24], our work considers the decomposition of the problem into the two Layer Building and Bin Building phases, but we additionally provide a detailed mathematical formulation of the practical constraints such as item support, bin stability, and load bearing for the application of the method in the logistic field.…”

Section: B Paper Contributionsmentioning

confidence: 99%

“…The objective in (22) is to minimize the number of bins to be composed, given the set of layers. Constraints (23) ensure the consistency between binary variables v j,k (∀ j ) and n k for each bin k, i.e., if any layer is assigned to a bin, the bin is considered not empty. Constraints (24) make sure that each layer can be part at most of one bin.…”

Section: B Bin Building Sub-problemmentioning

confidence: 99%

See 2 more Smart Citations

Automating Bin Packing: A Layer Building Matheuristics for Cost Effective Logistics

Tresca

Cavone

Carli

et al. 2022

IEEE Trans. Automat. Sci. Eng.

View full text Add to dashboard Cite

In this paper, we address the problem of automating the definition of feasible pallets configurations. This issue is crucial for the competitiveness of logistic companies and is still one of the most difficult problems in internal logistics. In fact, it requires the fast solution of a three-dimensional Bin Packing Problem (3D-BPP) with additional logistic specifications that are fundamental in real applications. To this aim, we propose a matheuristics that, given a set of items, provides feasible pallets configurations that satisfy the practical requirements of items' grouping by logistic features, load bearing, stability, height homogeneity, overhang as well as weight limits, and robotized layer picking. The proposed matheuristics combines a mixed integer linear programming (MILP) formulation of the 3D-Single Bin-Size BPP (3D-SBSBPP) and a layer building heuristics. In particular, the feasible pallets configurations are obtained by sequentially solving two MILP sub-problems: the first, given the set of items to be packed, aims at minimizing the unused space in each layer and thus the number of layers; the latter aims at minimizing the number of shipping bins given the set of layers obtained from the first problem. The approach is extensively tested and compared with existing approaches. For its validation we use both realistic data-sets drawn from the literature and real data-sets, obtained from an Italian logistics leader. The resulting outcomes show the effectiveness of the method in providing high-quality bin configurations in short computational times. Note to Practitioners-This work is motivated by the intentionof facilitating the transition from Logistics 3.0 to Logistics 4.0 by providing an effective tool to automate bin packing, suitable for automated warehouses. On the one hand, the proposed technique provides stable and compact bin configurations in less than half a minute per bin on average, despite the high computational complexity of the 3D-SBSBPP. On the other hand, the approach allows to consider compatibility constraints for the items (e.g., final customer and category of the items), and the use of robotized layer picking in automated warehouses. In effect, layers composed by only one type of items (i.e., monoitem layers) can be directly picked and placed on the pallet by a robotic arm without the intervention of any operator. Consequently, the adoption of this approach in warehouses could drastically improve the efficiency of the packing process.

show abstract

Section: A Related Work On 3d-bppmentioning

confidence: 99%

Section: B Paper Contributionsmentioning

confidence: 99%

Section: B Bin Building Sub-problemmentioning

confidence: 99%

See 1 more Smart Citation

Automating Bin Packing: A Layer Building Matheuristics for Cost Effective Logistics

Tresca

Cavone

Carli

et al. 2022

IEEE Trans. Automat. Sci. Eng.

View full text Add to dashboard Cite

show abstract

“…The second explore methods of assigning and positioning a set of cargo items into different containers. Primary works along these lines include Chen et al [11], Padberg [12], Fasano [13], Yan et al [14], Liu et al [15], Li et al [16], Tang [17], Paquay et al [18][19][20][21], Trivella and Pisinger [22], and Sun et al [44]. In the present work, we focus on the third case, that is, the aircraft WBP.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimization approach to the aircraft weight and balance problem with the centre of gravity envelope constraints

Zhao

Yuan

Dong

et al. 2021

IET Intelligent Trans Sys

View full text Add to dashboard Cite

The aircraft weight and balance problem (WBP) defined in terms of selecting unit load devices (ULDs) from an available set and allocating them to specified positions in cargo holds. It is critical to aircraft safety as well as operational efficiency and profit. It is an NPhard problem combining characteristics of the knapsack problem and generalized assignment problems, as well as complex practical constraints. A mixed integer programming model is constructed to maximize the total payload and minimize the center of gravity (CG) deviation by considering the constraints of positions, weights, balance etc. In contrast to prior studies using a constant delta to limit CG deviation, a new set of CG envelope constraints is proposed based on the variation in actual CG under different statuses and precise describing CG. A linearizing strategy is further designed to simplify the nonlinear CG envelope constraints. The proposed model can be solved using commercial optimization software within a few seconds and maintain the CG within the designated CG envelope in all test instances; in contrast, the other (CG deviation-based) method may result in flight hazards in some scenarios.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

“…Crainic et al (2011) presented GASP greedy adaptive search approach: metaheuristics able to efficiently address two and three-dimensional multi-container packing problems. Paquay et al (2018) described a tailored constructive heuristic for real-life instances of three-dimensional (MBSBPP) in Aircraft Company. Sumetthapiwat et al (2020) deal with multi stock sizes and fixed-size usable leftovers for the two-stage two-dimensional cutting stock problem.…”

Section: Introductionmentioning

confidence: 99%

An Efficient Constructive Heuristic for the Cutting Stock Problem Applied in a Foam Mattress Industry

Baazaoui

Elleuch

Kamoun³

2022

International Journal of Applied Metaheuristic Computing

View full text Add to dashboard Cite

The cutting and packing problem belongs to the combinatorial optimization problems; it covers a wide range of practical cases in industries. The present paper investigates a new real world problem needs to be solved through a daily operations of cutting foam blocks in an industrial company. The problem is considered as one of non-classical problems in the cutting and packing area. It represents a variant of the three dimensional Cutting Stock Problem. The originality of the studied problem is indicated by a specific set of constraints related to the production process and the cutting ways. A constructive heuristic was developed to provide cutting patterns in advance. All possible combinations established from the ways of cutting right rectangular prisms from foam blocks define the cutting patterns. This heuristic performs well and shows promising results in reasonable computational times to provide efficient cutting plans in order to reduce the total material loss.

show abstract

MIP-based constructive heuristics for the three-dimensional Bin Packing Problem with transportation constraints

Cited by 36 publications

References 19 publications

Automating Bin Packing: A Layer Building Matheuristics for Cost Effective Logistics

Automating Bin Packing: A Layer Building Matheuristics for Cost Effective Logistics

Optimization approach to the aircraft weight and balance problem with the centre of gravity envelope constraints

An Efficient Constructive Heuristic for the Cutting Stock Problem Applied in a Foam Mattress Industry

Contact Info

Product

Resources

About