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Filters
Revisiting the Cardinality Reasoning for BinPacking Constraint
[chapter]
2013
Lecture Notes in Computer Science
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In a previous work, we introduced a filtering for the Bin-Packing constraint based on a cardinality reasoning for each bin combined with a global cardinality constraint. ...
We improve this filtering with an algorithm providing tighter bounds on the cardinality variables. ...
For each instance, we test three different filtering configurations for bin-packing:-A: The BinPacking constraint from [8] + a GCC constraint, -B: A + the cardinality filtering from [7], -C: A + the cardinality ...
doi:10.1007/978-3-642-40627-0_43
fatcat:ofggkwqh6rcyjdyye7s5y26efy
Cardinality Reasoning for Bin-Packing Constraint: Application to a Tank Allocation Problem
[chapter]
2012
Lecture Notes in Computer Science
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This paper considers the use of a cardinality/flow reasoning for improving the filtering of a bin-packing constraint. ...
The cardinality reasoning of the redundant GCC makes deductions that the bin-packing constraint cannot see since the placement of all items into every bin is considered at once rather than for each bin ...
Cardinality reasoning for bin-packing Existing filtering algorithms for the BinP acking constraint do not make use of the cardinality information inside each bin (i.e.. the number of items packed inside ...
doi:10.1007/978-3-642-33558-7_58
fatcat:o4okrlkiyvdztj52qgk2kwudmq
Solving Steel Mill Slab Problems with constraint-based techniques: CP, LNS, and CBLS
2010
Constraints
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Gargani and Refalo solved the problem using Large Neighborhood Search and Van Hentenryck and Michel made use of constraint programming with an improved symmetry breaking scheme. ...
The Steel Mill Slab Problem is an optimization benchmark that has been studied for a long time in the constraint-programming community but was only solved efficiently in the two last years. ...
Improving the CP Model with a Global Symmetric Cardinality Constraint This section improves the model by introducing a global constraint to express the color constraints allowing a stronger filtering of ...
doi:10.1007/s10601-010-9100-5
fatcat:mn2rzrhzyfbirhvzghwc3ffofq
Global Constraints: A Survey
[chapter]
2010
Hybrid Optimization
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Constraint programming (CP) is mainly based on filtering algorithms; their association with global constraints is one of the main strengths of CP because they exploit the specific structure of each constraint ...
We recall that each person has to be associated with exactly one activity. Encoding the problem with a set of atmost/atleast constraints leads to no deletion. ...
This category contains constraints which are associated with some costs, like the cardinality with cost (cost-gcc), the shorter path, the knapsack, bin-packing... ...
doi:10.1007/978-1-4419-1644-0_3
fatcat:e4brsuizdrcjrdg4nfltvnowiq
Filtering Atmost1 on Pairs of Set Variables
[chapter]
2008
Lecture Notes in Computer Science
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We present an efficient filtering algorithm, establishing bounds consistency, for the atmost1 constraint on pairs of set variables with fixed cardinality. ...
The Atmost1 Constraint on Pairs of Set Variables The atmost1 constraint was introduced by Sadler and Gervet [5] and specifies, for a collection of n set variables with given cardinalities, that each ...
doi:10.1007/978-3-540-68155-7_42
fatcat:66u337hqfvfcvmaene2k2vmzau
The BIN_COUNTS Constraint: Filtering and Applications
[article]
2016
arXiv
pre-print
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We introduce the BIN_COUNTS constraint, which deals with the problem of counting the number of decision variables in a set which are assigned values that lie in given bins. ...
We show that BIN_COUNTS can be employed to develop a decomposition for the χ^2 test constraint, a new statistical constraint that we introduce in this work. ...
We show that the constraint matrix is totally unimodular (TUM); this implies that feasible region associated with the system of linear equations is an integral polyhedron [40] . ...
arXiv:1611.08942v5
fatcat:b7vhqcwdefewfp5w6nc4prth7m
Bin Packing with Linear Usage Costs – An Application to Energy Management in Data Centres
[chapter]
2013
Lecture Notes in Computer Science
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Second, we present a column generation model for computing the lower bound on the original energy management problem where the pricing problem is essentially a cost-aware bin packing with side constraints ...
We study lower bounds based on Linear Programming and extend the bin packing global constraint with cost information. ...
The pricing problem for period t can now be seen as a cost-aware bin packing problem with an extra cost related to the number of items assigned to a bin and two side constraints: a cardinality and memory ...
doi:10.1007/978-3-642-40627-0_7
fatcat:c3q2sz4jyjhdfallf6jmjhsygy
Bin Completion Algorithms for Multicontainer Packing, Knapsack, and Covering Problems
2007
The Journal of Artificial Intelligence Research
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For the bin packing problem, we demonstrate significant improvements compared to most previous results, but show that bin completion is not competitive with current state-of-the-art cutting-stock based ...
We propose bin completion, a branch-and-bound strategy for one-dimensional, multicontainer packing problems. ...
Acknowledgments Thanks to Gleb Belov for running his solver on some of our bin packing test instances. The anonymous reviewers provided many helpful comments and suggestions that improved this paper. ...
doi:10.1613/jair.2106
fatcat:tqle57hehvfujnschpxrcvbea4
Solving Problems with CP: Four Common Pitfalls to Avoid
[chapter]
2011
Lecture Notes in Computer Science
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Constraint Programming (CP) is a general technique for solving combinatorial optimization problems. ...
Mainly, there are: the abstraction of interesting and relevant subparts, the definition of benchmarks and design of a global model and the application of a particular search strategy. ...
It changes the kind of problem which is solved. With such data sets, we can only conclude about problems involving only few items per bins and not for the bin packing problem in general. ...
doi:10.1007/978-3-642-23786-7_3
fatcat:mizoer5yuffj5jip5tfvlqqmdy
On the Use of Equivalence Classes for Optimal and Suboptimal Bin Packing and Bin Covering
2020
IEEE Transactions on Automation Science and Engineering
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The optimization problem concerns minimizing, for bin packing, or maximizing, for bin covering, the number of bins. ...
The problem concerns a set of items, each with its own value, that are to be sorted into bins in such a way that the total value of each bin, as measured by the sum of its item values, is not above (for ...
ACKNOWLEDGEMENTS The authors thank Folkmar Frederik Ramcke for implementing the algorithms for package generation. ...
doi:10.1109/tase.2020.3022986
fatcat:oeevrcolazamfcttncn6qg6xqi
Variable Objective Large Neighborhood Search: A Practical Approach to Solve Over-Constrained Problems
2013
2013 IEEE 25th International Conference on Tools with Artificial Intelligence
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Everyone having used Constraint Programming (CP) to solve hard combinatorial optimization problems with a standard exhaustive Branch & Bound Depth First Search (B&B DFS) has probably experienced scalability ...
We suggest extending the Large Neighborhood Search (LNS) framework enabling it with the possibility of changing dynamically the objective function along the restarts. ...
This work does not attempt to improve the poor communication of sum constraints with other constraints in the constraint store as was proposed in [20] . ...
doi:10.1109/ictai.2013.147
dblp:conf/ictai/Schaus13
fatcat:b34gqjo5jrdcdjmh72v725ojn4
Global Constraints and Filtering Algorithms
[chapter]
2004
Operations Research/Computer Science Interfaces Series
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In addition, the filtering algorithms establishing arc consistency for two useful constraints, the alldiff and the global cardinality constraints, are fully detailed. ...
Constraint programming (CP) is mainly based on filtering algorithms; their association with global constraints is one of the main strengths of CP. This chapter is an overview of these two techniques. ...
Some medium filtering algorithms have also been developed for some constraints like global cardinality constraint with costs, and symmetric alldiff. Thus, these algorithms can be improved. ...
doi:10.1007/978-1-4419-8917-8_4
fatcat:xwkvlamj6veexazns7xagttyzm
Approximating Poisson Disk Distributions by Means of a Stochastic Dither Array
[article]
2010
Computer Graphics and Visual Computing
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The image-based field of digital halftoning can provide additional tools for graphics researchers and practitioners. ...
Further, the ability of dither array construction techniques to shape spectral characteristics of dot patterns is shown with several variations of design parameters. ...
We thank Thomas Schlömer for providing point set analysis source code in the public domain. ...
doi:10.2312/localchapterevents/tpcg/tpcg10/083-090
dblp:conf/tpcg/AlfordS10
fatcat:7l5nbdv72veeziyncdnrfturbe
The Objective Sum Constraint
[chapter]
2011
Lecture Notes in Computer Science
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Therefore, ad-hoc techniques are designed for pruning the global objective variable by taking account of the interactions between constraints defined on local objective variables. ...
In this paper, we propose a new global constraint which deals with this issue in a generic way. ...
For instance, it occurs in multidimensional bin packing problems (in which an item has several dimensions), like the one appearing in the cloud computing management. ...
doi:10.1007/978-3-642-21311-3_18
fatcat:veawz3al5jf7fdyqyqyvfwts5u
Cost-aware Integration Process Modeling in Multiclouds
[article]
2021
arXiv
pre-print
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While multicloud settings gain importance, their promised freedom of selecting the best option for a specific problem is currently not realized as well as security constraints are handled in a cost-intensive ...
In this work, we propose a design-time placement for processes in multiclouds that is cost-optimal for INTaaS problem sizes, and respects configurable security constraints of their customers. ...
Acknowledgements We thank Jasmin Greissl for various valuable discussions in the context of this article and Dr. Fredrik Nordvall Forsberg for proofreading. ...
arXiv:2103.08675v2
fatcat:vji5kad63bh6rm3cfx3vuhdsqi
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