Approximation Algorithms for Time Constrained Scheduling

Jansen, Klaus; Öhring, Sabine R.

doi:10.1006/inco.1996.2616

Cited by 69 publications

(18 citation statements)

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“…The IP‐based perturbation and restricted local search procedures proposed in this paper could also be used to solve large instances of related problems, such as the MRGAP (Gavish and Pirkul, ), the BPPC (Jansen and Öhring, ), the multicapacity bin packing problem (Masson et al., ), and load rebalancing problem (Chen et al., ). The results of our heuristics for MRP could be improved by smaller and tighter mathematical formulations, which would allow the heuristics to solve larger subproblems at each iteration.…”

Section: Discussionmentioning

confidence: 99%

“…Another problem related to MRP is the bin packing problem with conflicts (BPPC; Jansen and Öhring, ). Given a set of items with sizes and a conflict graph, BPPC seeks a partition of the items into independent sets over the conflict graph, where the number of independent sets is minimized.…”

Section: Introductionmentioning

confidence: 99%

“…Given a set of items with sizes and a conflict graph, BPPC seeks a partition of the items into independent sets over the conflict graph, where the number of independent sets is minimized. Jansen and Öhring () proposed approximation algorithms for BPPC, whereas Gendreau et al. () proposed heuristics and developed valid lower bounds.…”

Section: Introductionmentioning

confidence: 99%

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Heuristics and matheuristics for a real‐life machine reassignment problem

Lopes

Morais

Noronha

et al. 2014

Int Trans Operational Res

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This paper addresses a real-life machine reassignment problem proposed in the Google ROADEF/EURO Challenge (2012). In this paper, we propose a linear integer programming (IP) formulation and iterated local search (ILS) heuristics for approximately solving this problem. Different versions of the ILS heuristics are presented. Two of these versions rely on IP-based perturbations, whereas the other two are based on randomized perturbations. We also propose efficient restricted versions of the classic perturbation and local search procedures based on the "shift" and "swap" neighborhoods. Computational experiments showed that the IP-based heuristics are competitive with the best heuristics in the literature.Keywords: machine reassignment problem; iterated local search; heuristics; linear integer programming R. Lopes et al. / Intl. Trans. in Op. Res. 22 (2015) 77-95 The "capacity constraints" guarantee that all machines have enough available resources to run the processes assigned to them. Let C mr ∈ N be the capacity of a resource r ∈ R for a machine m ∈ M and D pr ∈ N be the demand of r for a process p ∈ P, the capacity constraints can be formulated aswhere U (m, r) = p∈P|X (p)=m D pr is the usage of r for m according to the reassignment X . We avoid the notation U (m, r, X ) and write U (m, r) for the sake of a cleaner notation. We use same notations for all the functions that depend on X . A resource r ∈ R is said "transient" if it is reserved for a process p ∈ P simultaneously on machines I p and X (p). For example, the disk space used by p in I p can only be freed after the migration of p to X (p) has finished, meanwhile this resource must be reserved for p in both machines. The "transient constraints" are extensions of the capacity constraints for transient resources. Let T ⊆ R be the set of transient resources, the transient constraints can be stated as p∈P|I p =m∨X (p)=m

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Heuristics and matheuristics for a real‐life machine reassignment problem

Lopes

Morais

Noronha

et al. 2014

Int Trans Operational Res

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“…Conflicts between individual pairs of objects have been introduced to the BPP by Jansen & Öhring (1997). The authors propose and evaluate different approximation algorithms for solving the BPC, relying on a conflict graph.…”

Section: Literature Reviewmentioning

confidence: 99%

A variable neighborhood search algorithm for the bin packing problem with compatible categories

Santos

Iwayama

Cavalcanti

et al. 2019

Expert Systems with Applications

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“…BPPC has been shown to be APXhard (it is not approximable with a ratio less than 1.5; see [31]). One of the primary sources of BPPC is [32]. A recent branch-and-price approach for BPPC is analyzed in [33].…”

Section: Related Workmentioning

confidence: 99%

A Replication Scheme for Multiple Fragmentations with Overlapping Fragments

Wiese

Waage

Bollwein

2016

The Computer Journal

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In this article, we introduce a replication procedure in a distributed database system that supports several fragmentations of the same data table. One application that requires multiple fragmentations is flexible (similarity-based) query answering. The major feature of our replication procedure is that replication and recovery respect the overlaps of fragments stemming from different fragmentations. In this paper we extend the data replication problem (DRP) by not only considering hard constraints to ensure a fixed replication factor but also adding soft constraints that express desired data locality of fragments. We furthermore analyze the case that there are more fragmentations (leading to the situation that some replication conditions are optional); and we study the influences of data updates (insertions and deletions) on the data distribution.

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Approximation Algorithms for Time Constrained Scheduling

Cited by 69 publications

References 6 publications

Heuristics and matheuristics for a real‐life machine reassignment problem

Heuristics and matheuristics for a real‐life machine reassignment problem

A variable neighborhood search algorithm for the bin packing problem with compatible categories

A Replication Scheme for Multiple Fragmentations with Overlapping Fragments

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