A new polynomial-time algorithm for linear programming
Combinatorica
Integer and combinatorial optimization
Integer and combinatorial optimization
A practical use of Jackson's preemptive schedule for solving the job shop problem
Annals of Operations Research
Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Minimizing conflicts: a heuristic repair method for constraint satisfaction and scheduling problems
Artificial Intelligence - Special volume on constraint-based reasoning
A lift-and-project cutting plane algorithm for mixed 0-1 programs
Mathematical Programming: Series A and B
Optimal speedup of Las Vegas algorithms
Information Processing Letters
A filtering algorithm for constraints of difference in CSPs
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Noise strategies for improving local search
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Randomized algorithms
Logic-based 0-1 constraint programming
Logic-based 0-1 constraint programming
Disjunctive programming and cooperating solvers
Advances in computational and stochastic optimization, logic programming, and heuristic search
Boosting combinatorial search through randomization
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
On the run-time behaviour of stochastic local search algorithms for SAT
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Heavy-Tailed Phenomena in Satisfiability and Constraint Satisfaction Problems
Journal of Automated Reasoning
Generating Satisfiable Problem Instances
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Search Strategies for Hybrid Search Spaces
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Combining local and global search in a constraint programming environment
The Knowledge Engineering Review
A scheme for unifying optimization and constraint satisfaction methods
The Knowledge Engineering Review
Combining satisfiability techniques from AI and OR
The Knowledge Engineering Review
Bridging the gap between planning and scheduling
The Knowledge Engineering Review
Applying integer programming to AI planning
The Knowledge Engineering Review
Integer optimization models of AI planning problems
The Knowledge Engineering Review
Problem structure in the presence of perturbations
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Stochastic procedures for generating feasible schedules
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Summarizing CSP hardness with continuous probability distributions
AAAI'97/IAAI'97 Proceedings of the fourteenth national conference on artificial intelligence and ninth conference on Innovative applications of artificial intelligence
Generalized arc consistency for global cardinality constraint
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
On the intersection of AI and OR
The Knowledge Engineering Review
Sensitivity analysis for distributed optimization with resource constraints
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Integrating AI and OR: an industrial engineering perspective
ADVIS'04 Proceedings of the Third international conference on Advances in Information Systems
Distributed reasoning for multiagent simple temporal problems
Journal of Artificial Intelligence Research
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Both the Artificial Intelligence (AI) and the Operations Research (OR) communities are interested in developing techniques for solving hard combinatorial problems, in particular in the domain of planning and scheduling. AI approaches encompass a rich collection of knowledge representation formalisms for dealing with a wide variety of real-world problems. Some examples are constraint programming representations, logical formalisms, declarative and functional programming languages such as Prolog and Lisp, Bayesian models, rule-based formalism, etc. The downside of such rich representations is that in general they lead to intractable problems, and we therefore often cannot use such formalisms for handling realistic size problems. OR, on the other hand, has focused on more tractable representations, such as linear programming formulations. OR-based techniques have demonstrated the ability to identify optimal and locally optimal solutions for well-defined problem spaces. In general, however, OR solutions are restricted to rigid models with limited expressive power. AI techniques, on the other hand, provide richer and more flexible representations of real-world problems, supporting efficient constraint-based reasoning mechanisms as well as mixed initiative frameworks, which allow the human expertise to be in the loop. The challenge lies in providing representations that are expressive enough to describe real-world problems and at the same time guaranteeing good and fast solutions.