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Manipulating MDD Relaxations for Combinatorial Optimization [chapter]

David Bergman, Willem-Jan van Hoeve, John N. Hooker
2011 Lecture Notes in Computer Science  
We study the application of limited-width MDDs (multivalued decision diagrams) as discrete relaxations for combinatorial optimization problems.  ...  We introduce a new compilation method for constructing such MDDs, as well as algorithms that manipulate the MDDs to obtain stronger relaxations and hence provide stronger lower bounds.  ...  In this paper, we examine the use of BDDs and MDDs as relaxations for combinatorial optimization problems.  ... 
doi:10.1007/978-3-642-21311-3_5 fatcat:qugl7k7cqjbfpigkkdy5d3cgzi

What's Hot at CPAIOR (Extended Abstract)

Claude-Guy Quimper
2017 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
(Perez and Régin 2016) improve the manipulation of Multi-Valued Decision Diagrams (MDD) by proposing a new algorithm that builds a MDD from a list of tuples.  ...  They also propose new in-place algorithms that insert or delete tuples from an existing MDD. Finally, they show how to efficiently reduce the size of a MDD.  ... 
doi:10.1609/aaai.v31i1.10640 fatcat:nsvn7tyaznb6pnsakg75myszri

MDD Propagation for Sequence Constraints

D. Bergman, A. A. Cire, W. Van Hoeve
2014 The Journal of Artificial Intelligence Research  
Our first contribution is proving that establishing MDD-consistency for Sequence is NP-hard.  ...  We study propagation for the Sequence constraint in the context of constraint programming based on limited-width MDDs.  ...  The domain propagator for sequence has been implemented in IBM-ILOG CP Optimizer 1.6.  ... 
doi:10.1613/jair.4199 fatcat:ahpaheouorb3dobz435wlrnjky

Decision Diagrams for Discrete Optimization: A Survey of Recent Advances [article]

Margarita P. Castro, Andre A. Cire, J. Christopher Beck
2022 arXiv   pre-print
In the last decade, decision diagrams (DDs) have been the basis for a large array of novel approaches for modeling and solving optimization problems.  ...  We discuss the main advantages of DDs, point out major challenges, and provide directions for future work.  ...  Moreover, Haddock has comparable performance when compared to dedicated MDD propagators for different constraints.  ... 
arXiv:2201.11536v1 fatcat:esoh7tnrh5ad3o7rjhvdq22374

Interactive Cost Configuration Over Decision Diagrams

H. R. Andersen, T. Hadzic, D. Pisinger
2010 The Journal of Artificial Intelligence Research  
We also discuss the effect on MDD size if the cost function is non-additive or if it is encoded explicitly into MDD.  ...  Response times are generally within a fraction of a second even for very large instances.  ...  We would also like to thank Erik van der Meer for providing the T-shirt example.  ... 
doi:10.1613/jair.2905 fatcat:7w6b5yi6hvg5pliog3lpiq5sam

A New Boolean Encoding for MAPF and its Performance with ASP and MaxSAT Solvers

Roberto Javier Asín Achá, Rodrigo López, Sebastián Hagedorn, Jorge A. Baier
2021 Symposium on Combinatorial Search  
As such, dense maps may be very hard to solve optimally.  ...  For MaxSAT, we study different ways in which we may combine the MSU3 and LSU algorithms for maximum performance.  ...  We presented a new Boolean encoding for SOC-optimal MAPF. We studied extensively how this encoding can be exploited within MaxSAT solvers. The encoding is compact.  ... 
dblp:conf/socs/AchaLHB21 fatcat:6inz3gvzovcpbj5cl3k5grtwim

Planning and Operations Research (Dagstuhl Seminar 18071)

J. Christopher Beck, Daniele Magazzeni, Gabriele Röger, Willem-Jan Van Hoeve, Michael Wagner
2018 Dagstuhl Reports  
All three areas have in common that they deal with complex systems where a huge space of interacting options makes it almost impossible to humans to take optimal or even good decisions.  ...  ) industrial applications while planning and constraint programming emerged as subfields of artificial intelligence where the emphasis was traditionally more on symbolic and logical search techniques for  ...  Relaxed MDDs can also be used to represent the whole problem. Ongoing work in Toronto builds an MDD and extracts relaxed solutions from it, unrolling the MDD until an actual solution is found.  ... 
doi:10.4230/dagrep.8.2.26 dblp:journals/dagstuhl-reports/BeckMRH18 fatcat:lavt5jfujfarfmtwrpbbxan2oq

Efficient Message Passing for 0-1 ILPs with Binary Decision Diagrams [article]

Jan-Hendrik Lange, Paul Swoboda
2021 arXiv   pre-print
We present experimental results on combinatorial problems from MAP inference for Markov Random Fields, quadratic assignment, discrete tomography and cell tracking for developmental biology and show promising  ...  We present a message passing method for 0-1 integer linear programs.  ...  Introduction Structured prediction tasks in machine learning commonly require solving relaxations of NP-hard combinatorial optimization problems that are formulated as integer linear programs (ILPs).  ... 
arXiv:2009.00481v2 fatcat:aq3kyrwrkbe2dfpjy4fekhpdvq

Biconditional Binary Decision Diagrams: A Novel Canonical Logic Representation Form

Luca Amaru, Pierre-Emmanuel Gaillardon, Giovanni De Micheli
2014 IEEE Journal on Emerging and Selected Topics in Circuits and Systems  
We provide, in this paper, a solid ground for BBDDs by studying their underlying theory and manipulation properties.  ...  Empowered by reduction and ordering rules, BBDDs are remarkably compact and unique for a Boolean function.  ...  The combinatorial verification of the optimized design is also speeded-up by 11 .3% using BBDDs in place of standard BDDs.  ... 
doi:10.1109/jetcas.2014.2361058 fatcat:odgpqsnwrncwbogbnbilvshdiq

Algebraic manipulation of scientific datasets

Bill Howe, David Maier
2005 The VLDB journal  
Existing approaches for manipulating these datasets are incomplete: The performance of SQL queries for manipulating large numeric datasets is not competitive with specialized tools.  ...  In this paper, we present an algebra of gridfields for manipulating both regular and irregular gridded datasets, algebraic optimization techniques, and an implementation backed by experimental results.  ...  Berti observes that combinatorial algorithms for grid manipulation are superior to geometric algorithms [3] . • Aggregation.  ... 
doi:10.1007/s00778-005-0157-5 fatcat:3pecdepnpreepfv2whzkaliq6q

Algebraic Manipulation of Scientific Datasets [chapter]

B HOWE, D MAIER
2004 Proceedings 2004 VLDB Conference  
Existing approaches for manipulating these datasets are incomplete: The performance of SQL queries for manipulating large numeric datasets is not competitive with specialized tools.  ...  In this paper, we present an algebra of gridfields for manipulating both regular and irregular gridded datasets, algebraic optimization techniques, and an implementation backed by experimental results.  ...  Berti observes that combinatorial algorithms for grid manipulation are superior to geometric algorithms [3] . • Aggregation.  ... 
doi:10.1016/b978-012088469-8/50081-4 fatcat:mja23zxxfnb4hiktaoofctzf4q

Algebraic Manipulation of Scientific Datasets [chapter]

Bill Howe, David Maier
2004 Proceedings 2004 VLDB Conference  
Existing approaches for manipulating these datasets are incomplete: The performance of SQL queries for manipulating large numeric datasets is not competitive with specialized tools.  ...  In this paper, we present an algebra of gridfields for manipulating both regular and irregular gridded datasets, algebraic optimization techniques, and an implementation backed by experimental results.  ...  Berti observes that combinatorial algorithms for grid manipulation are superior to geometric algorithms [3] . • Aggregation.  ... 
doi:10.1016/b978-012088469-8.50081-4 dblp:conf/vldb/HoweM04 fatcat:tuozsbs7mfd3dlomusfbimht5q

Adversarial Attacks against Reinforcement Learning-based Portfolio Management Strategy

Yu-Ying Chen, Chiao-Ting Chen, Chuan-Yun Sang, Yao-Chun Yang, Szu-Hao Huang
2021 IEEE Access  
Researches have rarely focused on planning for long-term attacks against RL-based trading systems.  ...  Enhanced EIIE was then applied to the adversarial agent for the agent to learn when and how much to attack (in the form of introducing perturbations).In our experiments, our proposed adversarial attack  ...  The above optimization can be relaxed by using the corresponding Lagrangianrelaxed form: arg min ρ L(C(x adv ), y target ) + λ|ρ p ( 2 ) where λ is a hyper-parameter controlling the strength of the distance  ... 
doi:10.1109/access.2021.3068768 fatcat:wkvbhjffevfktk42jscwhu2c2i

Model-based evaluation: from dependability to security

D.M. Nicol, W.H. Sanders, K.S. Trivedi
2004 IEEE Transactions on Dependable and Secure Computing  
A wide array of model-based evaluation techniques are now available, ranging from combinatorial methods, which are useful for quick, rough-cut analyses, to state-based methods, such as Markov reward models  ...  The development of techniques for quantitative, model-based evaluation of computer system dependability has a long and rich history.  ...  Jenny Applequist for her editorial assistance.  ... 
doi:10.1109/tdsc.2004.11 fatcat:nli5cwcxrbfchkzhvojdttwpym

Decision Diagrams for Optimization

Andre Augusto Cire
2018
Recently, they have been considered for a variety of purposes in optimization and operations research.  ...  We then present a branching scheme that exploits the recursive structure of an approximate diagram, establishing a novel generic solver for discrete optimization problems.  ...  Much of the research effort dedicated to developing heuristics for discrete optimization has primarily focused on specific combinatorial optimization problems.  ... 
doi:10.1184/r1/6715670.v1 fatcat:mbzttyad6nccldqkh34fwdsfu4
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