CP 2005 - PDF Preprint Papers

CP 2005 Principles and Practice of Constraint Programming

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CP
2005
Springer

192views Artificial Intelligence» more CP 2005»

Planning and Scheduling to Minimize Tardiness

13 years 10 months ago

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We combine mixed integer linear programming (MILP) and constraint programming (CP) to minimize tardiness in planning and scheduling. Tasks are allocated to facilities using MILP an...

John N. Hooker

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Id	Views	Title	Status

1	192	Planning and Scheduling to Minimize Tardiness	claim
2	164	Bounds-Consistent Local Search	claim
3	153	Solving Large-Scale Nonlinear Programming Problems by Constraint Partitioning	claim
4	152	Domain Reduction for the Circuit Constraint	claim
5	150	2-Way vs. d-Way Branching for CSP	claim
6	148	Automatic Detection of Variable and Value Symmetries	claim
7	148	Dynamic Ordering for Asynchronous Backtracking on DisCSPs	claim
8	147	Solving the Car-Sequencing Problem as a Non-binary CSP	claim
9	147	Approximations in Distributed Optimization	claim
10	141	Breaking All Value Symmetries in Surjection Problems	claim
11	140	Allocation and Scheduling for MPSoCs via Decomposition and No-Good Generation	claim
12	139	Tree Decomposition with Function Filtering	claim
13	139	Eplex: Harnessing Mathematical Programming Solvers for Constraint Logic Programming	claim
14	134	Applying Constraint Programming to Rigid Body Protein Docking	claim
15	129	Bounds of Graph Characteristics	claim
16	129	Conditional Symmetry Breaking	claim
17	129	Search and Inference in AI Planning	claim
18	126	Dimensioning an Inbound Call Center Using Constraint Programming	claim
19	125	Caching Search States in Permutation Problems	claim
20	122	Applying Decomposition Methods to Crossword Puzzle Problems	claim
21	122	Using Boolean Constraint Propagation for Sub-clauses Deduction	claim
22	121	CP(Graph): Introducing a Graph Computation Domain in Constraint Programming	claim
23	120	Extending Systematic Local Search for Job Shop Scheduling Problems	claim
24	120	AND/OR Branch-and-Bound for Solving Mixed Integer Linear Programming Problems	claim
25	118	On Solving Soft Temporal Constraints Using SAT Techniques	claim
26	117	A Linear-Logic Semantics for Constraint Handling Rules	claim
27	116	Encoding Requests to Web Service Compositions as Constraints	claim
28	115	Consistency for Quantified Constraint Satisfaction Problems	claim
29	114	Acquiring Parameters of Implied Global Constraints	claim
30	114	Probabilistic Arc Consistency	claim
31	113	Towards the Systematic Generation of Channelling Constraints	claim
32	111	Mind the Gaps: A New Splitting Strategy for Consistency Techniques	claim
33	111	Neighbourhood Clause Weight Redistribution in Local Search for SAT	claim
34	110	Multi-point Constructive Search	claim
35	110	Methods to Learn Abstract Scheduling Models	claim
36	110	Parallel Local Search in Comet	claim
37	110	Approximated Consistency for the Automatic Recording Problem	claim
38	108	Encoding HTN Planning as a Dynamic CSP	claim
39	106	Solution Equivalent Subquadrangle Reformulations of Constraint Satisfaction Problems	claim
40	105	Graph Invariants as Necessary Conditions for Global Constraints	claim
41	104	Mechanism Design for Preference Aggregation over Coalitions	claim
42	103	Distributed Constraints for Large-Scale Scheduling Problems	claim
43	102	Boosting Distributed Constraint Satisfaction	claim
44	101	Towards an Optimal CNF Encoding of Boolean Cardinality Constraints	claim
45	101	Approximate Constrained Subgraph Matching	claim
46	100	Automated Search for Heuristic Functions	claim
47	100	Constraint-Based Inference: A Bridge Between Constraint Processing and Probability Inference	claim
48	100	Search Heuristics and Heavy-Tailed Behaviour	claim
49	100	SPREAD: A Balancing Constraint Based on Statistics	claim
50	98	From Linear Relaxations to Global Constraint Propagation	claim
51	97	Solving Over-Constrained Problems with SAT	claim
52	97	Weak Symmetries in Problem Formulations	claim
53	96	Solving Simple Planning Problems with More Inference and No Search	claim
54	96	Evolving Variable-Ordering Heuristics for Constrained Optimisation	claim
55	95	Lookahead Saturation with Restriction for SAT	claim
56	95	Partial Redundant Modeling	claim
57	95	Test Instance Generation for MAX 2SAT	claim
58	94	Scheduling Social Tournaments	claim
59	92	A Constraint Based Agent for TAC-SCM	claim
60	91	Symmetry and Consistency	claim
61	90	Robust Constraint Solving Using Multiple Heuristics	claim
62	89	Incremental Algorithms for Local Search from Existential Second-Order Logic	claim
63	89	Local Consistency in Weighted CSPs and Inference in Max-SAT	claim
64	89	Using SAT in QBF	claim
65	88	Using Constraint Programming for Solving Distance CSP with Uncertainty	claim
66	87	Statistical Modelling of CSP Solving Algorithms Performance	claim
67	86	GOOSE - A Generic Object-Oriented Search Environment	claim
68	86	Speeding Up Constrained Path Solvers with a Reachability Propagator	claim
69	85	Sub-optimality Approximations	claim
70	85	Modeling Constraint Programs with Software Technology Standards	claim
71	82	Computing and Exploiting Tree-Decompositions for Solving Constraint Networks	claim
72	79	Tractable Clones of Polynomials over Semigroups	claim
73	79	Uncertainty in Soft Constraint Problems	claim
74	79	Full Arc Consistency in WCSP and in Constraint Hierarchies with Finite Domains	claim
75	71	Maintaining Longest Paths in Cyclic Graphs	claim
76	70	Randomization for Multi-agent Constraint Optimization	claim
77	57	Specialised Constraints for Stable Matching Problems	claim

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