MIP-based approaches for the container loading problem with multi-drop constraints

Junqueira, Leonardo; Morábito, Reinaldo; Yamashita, Denise Sato

doi:10.1007/s10479-011-0942-z

Cited by 57 publications

(30 citation statements)

References 25 publications

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“…We compare our algorithm with the exact procedure developed by Junqueira et al [30] using the 16 instances they generated. We also use the instances by Ceschia & Schaerf [10] in which they pack a single container.…”

Section: Computational Resultsmentioning

confidence: 99%

“…Their algorithm uses a scheme in which the next space to pack a box is randomly chosen among the list of empty spaces. Junqueira et al [30] develop an exact model to solve small instances of a container loading problem with multi-drop constraints. Their approach is based on a mixed integer linear programming model.…”

Section: Multi-drop Constraintsmentioning

confidence: 99%

“…• Boxes that are separated from those of other customers Junqueira et al [30] define reachability as a function of a parameter δ, which indicates how many units of length beyond the "border" between boxes of consecutive destinations the worker is allowed to go in order to unload the boxes. They define the "border" as a virtual wall defined after all boxes for a destination have been packed inside the container.…”

Section: Boxes That Are Touchablementioning

confidence: 99%

“…In this case these boxes would be left out of the loading. In Liu et al [33] and in Junqueira et al [30], the objective is to maximize the total volume packed, and this can be achieved by leaving out boxes for several customers.…”

Section: • Restrictedmentioning

confidence: 99%

“…We choose the value k at random from the interval [30,90]. The removed items plus the items that were left unpacked in the solution are then packed again using the deterministic constructive procedure.…”

Section: Improvementsmentioning

confidence: 99%

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

2015

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ABSTRACT. This paper studies a variant of the container loading problem in which to the classical geometric constraints of packing problems we add other conditions appearing in practical problems, the multidrop constraints. When adding multi-drop constraints, we demand that the relevant boxes must be available, without rearranging others, when each drop-off point is reached. We present first a review of the different types of multi-drop constraints that appear in literature. Then we propose a GRASP algorithm that solves the different types of multi-drop constraints and also includes other types of realistic constraints such as full support of the boxes and load bearing strength. The computational results validate the proposed algorithm, which outperforms the existing procedures dealing with multi-drop conditions and is also able to obtain good results for more standard versions of the container loading problem.

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Section: Computational Resultsmentioning

confidence: 99%

Section: Multi-drop Constraintsmentioning

confidence: 99%

Section: Boxes That Are Touchablementioning

confidence: 99%

Section: • Restrictedmentioning

confidence: 99%

Section: Improvementsmentioning

confidence: 99%

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