On online bin packing with LIB constraints

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On online bin packing with LIB constraints

In many applications of packing, the location of small items below large items, inside the packed boxes, is forbidden. We consider a variant of the classic online one dimensional bin packing, in which items allocated to each bin are packed there in the order of arrival, satisfying the condition above. This variant is called online bin packing problem with LIB (Larger Item in the Bottom) constra...

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Online bin packing with cardinality constraints revisited

Bin packing with cardinality constraints is a bin packing problem where an upper bound k ≥ 2 on the number of items packed into each bin is given, in addition to the standard constraint on the total size of items packed into a bin. We study the online scenario where items are presented one by one. We analyze it with respect to the absolute competitive ratio and prove tight bounds of 2 for any k...

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Online Bin Packing with Cardinality Constraints

We consider a one dimensional storage system where each container can store a bounded amount of capacity as well as a bounded number of items k ≥ 2. This defines the (standard) bin packing problem with cardinality constraints which is an important version of bin packing, introduced by Krause, Shen and Schwetman already in 1975. Following previous work on the unbounded space online problem, we e...

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Online Bin Packing with Cardinality Constraints Resolved

Cardinality constrained bin packing or bin packing with cardinality constraints is a basic bin packing problem. In the online version with the parameter k ≥ 2, items having sizes in (0, 1] associated with them are presented one by one to be packed into unit capacity bins, such that the capacities of bins are not exceeded, and no bin receives more than k items. We resolve the online problem in t...

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Performance Estimations of First Fit Algorithm for Online Bin Packing with Variable Bin Sizes and LIB constraints

We consider the NP Hard problem of online Bin Packing while requiring that larger (or longer) items be placed below smaller (or shorter) items — we call such a version the LIB version of problems. Bin sizes can be uniform or variable. We provide analytical upper bounds as well as computational results on the asymptotic approximation ratio for the first fit algorithm.

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ژورنال

عنوان ژورنال: Naval Research Logistics (NRL)

سال: 2009

ISSN: 0894-069X

DOI: 10.1002/nav.20383