Constraint programming and maths programming
The Knowledge Engineering Review
Branch-and-cut for combinatorial optimization problems without auxiliary binary variables
The Knowledge Engineering Review
Combining local and global search in a constraint programming environment
The Knowledge Engineering Review
Synthesis of efficient constraint-satisfaction programs
The Knowledge Engineering Review
Combining linear programming and satisfiability solving for resource planning
The Knowledge Engineering Review
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
Distributed reasoning for multiagent simple temporal problems
Journal of Artificial Intelligence Research
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This is the second of two special issues focusing on the integration of artificial intelligence (AI) and operations research (OR) techniques for solving hard computational problems, with an emphasis on planning and scheduling. Both the AI and the OR community have developed sophisticated techniques to tackle such challenging problems. OR has relied heavily on mathematical programming formulations such as integer and linear programming, while AI has developed constraint-based search techniques and inference methods. Recently, we have seen a convergence of ideas, drawing on the individual strengths of these paradigms.