001437587 000__ 05874cam\a2200625\i\4500
001437587 001__ 1437587
001437587 003__ OCoLC
001437587 005__ 20230309004156.0
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001437587 020__ $$a9783030782306$$q(electronic bk.)
001437587 020__ $$a3030782301$$q(electronic bk.)
001437587 020__ $$z9783030782290$$q(print)
001437587 0247_ $$a10.1007/978-3-030-78230-6$$2doi
001437587 035__ $$aSP(OCoLC)1257551972
001437587 040__ $$aGW5XE$$beng$$erda$$epn$$cGW5XE$$dOCLCO$$dOCLCF$$dEBLCP$$dOCLCQ$$dCOM$$dOCLCO$$dOCLCQ
001437587 049__ $$aISEA
001437587 050_4 $$aQA76.612$$b.C63 2021eb
001437587 08204 $$a005.1/16$$223
001437587 1112_ $$aInternational Conference on Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimisation Problems$$n(18th :$$d2021 :$$cVienna, Austria ; Online)
001437587 24510 $$aIntegration of constraint programming, artificial intelligence, and operations research :$$b18th International Conference, CPAIOR 2021, Vienna, Austria, July 5-8, 2021, Proceedings /$$cPeter J. Stuckey (ed.).
001437587 2463_ $$aCPAIOR 2021
001437587 264_1 $$aCham, Switzerland :$$bSpringer,$$c2021.
001437587 300__ $$a1 online resource (xvii, 468 pages) :$$billustrations (some color)
001437587 336__ $$atext$$btxt$$2rdacontent
001437587 337__ $$acomputer$$bc$$2rdamedia
001437587 338__ $$aonline resource$$bcr$$2rdacarrier
001437587 4901_ $$aLecture notes in computer science ;$$v12735
001437587 4901_ $$aLNCS sublibrary, SL 1, Theoretical computer science and general issues
001437587 500__ $$a" ... held in Vienna, Austria as a hybrid physical/virtual conference in response to the COVID-19 pandemic."--Preface
001437587 500__ $$aIncludes author index.
001437587 5050_ $$aSupercharging Plant Configurations using Z3 -- Why You Should Constrain Your Machine Learned Models -- Contextual Optimization: Bridging Machine Learning and Operations -- A Computational Study of Constraint Programming Approaches for Resource-Constrained Project Scheduling with Autonomous Learning Effects -- Strengthening of feasibility cuts in logic-based Benders decomposition -- Learning Variable Activity Initialisation for Lazy Clause Generation Solvers -- A*-based Compilation of Relaxed Decision Diagrams for the Longest Common Subsequence Problem -- Partitioning Students into Cohorts during COVID-19 -- A Two-Phases Exact Algorithm for Optimization of Neural Network Ensemble -- Complete Symmetry Breaking Constraints for the Class of Uniquely Hamiltonian Graphs -- Heavy-Tails and Randomized Restarting Beam Search in Goal-Oriented Neural Sequence Decoding -- Combining Constraint Programming and Temporal Decomposition Approaches -- Scheduling of an Industrial Formulation Plant -- The Traveling Social Golfer Problem: the case of the Volleyball Nations League -- Towards a Compact SAT-based Encoding of Itemset Mining Tasks -- A Pipe Routing Hybrid Approach based on A-Star Search and Linear Programming -- MDDs boost equation solving on discrete dynamical systems -- Variable Ordering for Decision Diagrams: A Portfolio Approach -- Two Deadline Reduction Algorithms for Scheduling Dependent Tasks on Parallel Processors -- Improving the Filtering of Branch-And-Bound MDD solver -- On the Usefulness of Linear Modular Arithmetic in Constraint Programming -- Injecting Domain Knowledge in Neural Networks: a Controlled Experiment on a Constrained Problem -- Learning Surrogate Functions for the Short-Horizon Planning in Same-Day Delivery Problems -- Between Steps: Intermediate Relaxations between big-M and Convex Hull Formulations -- Logic-Based Benders Decomposition for an Inter-modal Transportation Problem -- Checking Constraint Satisfaction -- Finding Subgraphs with Side Constraints -- Short-term scheduling of production fleets in underground mines using CP-based LNS -- Learning to Reduce State-Expanded Networks for Multi-Activity Shift Scheduling -- SeaPearl: A Constraint Programming Solver guided by Reinforcement Learning -- Learning to Sparsify Travelling Salesman Problem Instances -- Optimized Item Selection to Boost Exploration for Recommender Systems -- Improving Branch-and-Bound using Decision Diagrams and Reinforcement Learning -- Physician Scheduling During a Pandemic.
001437587 506__ $$aAccess limited to authorized users.
001437587 520__ $$aThis volume LNCS 12735 constitutes the papers of the 18th International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, CPAIOR 2021, which was held in Vienna, Austria, in 2021. Due to the COVID-19 pandemic the conference was held online. The 30 regular papers presented were carefully reviewed and selected from a total of 75 submissions. The conference program included a Master Class on the topic "Explanation and Verification of Machine Learning Models."
001437587 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed June 25, 2021).
001437587 650_0 $$aConstraint programming (Computer science)$$vCongresses.
001437587 650_0 $$aCombinatorial optimization$$xData processing$$vCongresses.
001437587 650_0 $$aArtificial intelligence$$vCongresses.
001437587 650_6 $$aProgrammation par contraintes$$vCongrès.
001437587 650_6 $$aOptimisation combinatoire$$xInformatique$$vCongrès.
001437587 650_6 $$aIntelligence artificielle$$vCongrès.
001437587 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001437587 655_7 $$aConference papers and proceedings.$$2lcgft
001437587 655_7 $$aActes de congrès.$$2rvmgf
001437587 655_0 $$aElectronic books.
001437587 7001_ $$aStuckey, Peter J.,$$eeditor.
001437587 830_0 $$aLecture notes in computer science ;$$v12735.
001437587 830_0 $$aLNCS sublibrary.$$nSL 1,$$pTheoretical computer science and general issues.
001437587 852__ $$bebk
001437587 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-78230-6$$zOnline Access$$91397441.1
001437587 909CO $$ooai:library.usi.edu:1437587$$pGLOBAL_SET
001437587 980__ $$aBIB
001437587 980__ $$aEBOOK
001437587 982__ $$aEbook
001437587 983__ $$aOnline
001437587 994__ $$a92$$bISE