CP 2004 - PDF Preprint Papers

CP 2004 Principles and Practice of Constraint Programming

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CP
2004
Springer

212views Artificial Intelligence» more CP 2004»

Heuristic Selection for Stochastic Search Optimization: Modeling Solution Quality by Extreme Value Theory

13 years 9 months ago

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The success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...

Vincent A. Cicirello, Stephen F. Smith

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Id	Views	Title	Status

1	212	Heuristic Selection for Stochastic Search Optimization: Modeling Solution Quality by Extreme Value Theory	claim
2	174	The Impact of AND/OR Search Spaces on Constraint Satisfaction and Counting	claim
3	164	Controllability of Soft Temporal Constraint Problems	claim
4	148	Counting-Based Look-Ahead Schemes for Constraint Satisfaction	claim
5	139	Challenges for Constraint Programming in Networking	claim
6	131	A Hybrid Method for Planning and Scheduling	claim
7	127	A Hyper-arc Consistency Algorithm for the Soft Alldifferent Constraint	claim
8	125	Hybrid Set Domains to Strengthen Constraint Propagation and Reduce Symmetries	claim
9	121	Concurrent Dynamic Backtracking for Distributed CSPs	claim
10	120	Decomposition and Learning for a Hard Real Time Task Allocation Problem	claim
11	118	The Cardinality Matrix Constraint	claim
12	114	Generating Robust Partial Order Schedules	claim
13	113	Disjoint, Partition and Intersection Constraints for Set and Multiset Variables	claim
14	113	Constraint-Based Combinators for Local Search	claim
15	112	The Tractability of Global Constraints	claim
16	110	Global Constraints for Integer and Set Value Precedence	claim
17	107	Improved Algorithms for the Global Cardinality Constraint	claim
18	107	ID Walk: A Candidate List Strategy with a Simple Diversification Device	claim
19	106	How Much Backtracking Does It Take to Color Random Graphs? Rigorous Results on Heavy Tails	claim
20	105	Statistical Regimes Across Constrainedness Regions	claim
21	105	Unary Resource Constraint with Optional Activities	claim
22	104	Full Dynamic Substitutability by SAT Encoding	claim
23	101	Constraint Propagation as a Proof System	claim
24	98	Leveraging the Learning Power of Examples in Automated Constraint Acquisition	claim
25	96	Understanding Random SAT: Beyond the Clauses-to-Variables Ratio	claim
26	95	A Domain Consistency Algorithm for the Stretch Constraint	claim
27	94	Computing the Frequency of Partial Orders	claim
28	94	Streamlined Constraint Reasoning	claim
29	93	A New Algorithm for Maintaining Arc Consistency After Constraint Retraction	claim
30	92	Backtrack-Free Search for Real-Time Constraint Satisfaction	claim
31	91	Set Variables and Local Search	claim
32	90	Deriving Filtering Algorithms from Constraint Checkers	claim
33	90	Completable Partial Solutions in Constraint Programming and Constraint-Based Scheduling	claim
34	87	Preprocessing Techniques for Distributed Constraint Optimization	claim
35	86	Solving the Crane Scheduling Problem Using Intelligent Search Schemes	claim
36	85	Quality of LP-Based Approximations for Highly Combinatorial Problems	claim
37	83	Speeding Up Constraint Propagation	claim
38	82	On-Demand Bound Computation for Best-First Constraint Optimization	claim
39	76	Strategies for Global Optimization of Temporal Preferences	claim
40	74	Variable Ordering Heuristics Show Promise	claim
41	71	Financial Portfolio Optimisation	claim

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