... This paper summarizes and contrasts the characteristics of the two fields; in particular, how they use logical inference in different ways, and how these ways can be combined. It sketches the intellectual background for recent e#orts at integration. It traces the history of logic-based methods in optimization and the development of constraint programming in artificial intelligence. It concludes with a review of recent research, with emphasis on schemes for integration, relaxation methods, and practical application
Although operations research (OR) and constraint programming (CP) have different roots, the links be...
. Constraints are an effective tool to define sets of data by means of logical formulae. Our goal he...
The constraint paradigm is a model of computation in which values are deduced whenever possible, und...
A pioneering look at the fundamental role of logic in optimization and constraint satisfaction Whil...
This chapter addresses the integration of constraints and search into programming lan-guages from th...
. This paper proposes a logic-based approach to optimization that combines solution methods from ma...
There has been a lot of interest lately from people solving constrained optimization problems for co...
Constraints support a programming style featuring declarative description and effective solving of s...
Constraint programming is an alternative approach to programming in which the programming process \u...
Optimization and constraint satisfaction methods are complementary to a large extent, and there has...
A logic view of 0-1 integer programming problems, providing new insights into the structure of probl...
A promising research line in the optimization community regards the hybridization of exact and heuri...
This paper presents constraint programming (CP) as a natural formalism for modelling problems, and a...
Constraint programming is a powerful paradigm for solving combinatorial search problems that draws o...
The paper describes how Constraint Based Reasoning (CBR) can be performed with two different paradig...
Although operations research (OR) and constraint programming (CP) have different roots, the links be...
. Constraints are an effective tool to define sets of data by means of logical formulae. Our goal he...
The constraint paradigm is a model of computation in which values are deduced whenever possible, und...
A pioneering look at the fundamental role of logic in optimization and constraint satisfaction Whil...
This chapter addresses the integration of constraints and search into programming lan-guages from th...
. This paper proposes a logic-based approach to optimization that combines solution methods from ma...
There has been a lot of interest lately from people solving constrained optimization problems for co...
Constraints support a programming style featuring declarative description and effective solving of s...
Constraint programming is an alternative approach to programming in which the programming process \u...
Optimization and constraint satisfaction methods are complementary to a large extent, and there has...
A logic view of 0-1 integer programming problems, providing new insights into the structure of probl...
A promising research line in the optimization community regards the hybridization of exact and heuri...
This paper presents constraint programming (CP) as a natural formalism for modelling problems, and a...
Constraint programming is a powerful paradigm for solving combinatorial search problems that draws o...
The paper describes how Constraint Based Reasoning (CBR) can be performed with two different paradig...
Although operations research (OR) and constraint programming (CP) have different roots, the links be...
. Constraints are an effective tool to define sets of data by means of logical formulae. Our goal he...
The constraint paradigm is a model of computation in which values are deduced whenever possible, und...