In this paper we propose a novel computational model for constraint logic programming (CLP) languages. The model provides an eecient mechanism for executing CLP programs by exploiting constraint satisfaction as a means for both solving constraints and controlling the whole computation. In the model, we separate constraint solving from the deduction procedure. Deductions over constraints are ext...

In this paper we introduce novel optimization methods for sequencing problems in which the setup times between a pair of tasks depend on the relative position of the tasks in the ordering. Our proposed methods rely on a hybrid approach where a constraint programming model is enhanced with two distinct relaxations: One discrete relaxation based on multivalued decision diagrams, and one continuou...

We propose to use bilattice as a constraint valuation structure in order to represent truth and belief at the same time. A bilattice is a set which owns two lattices orderings. They have been used in Artificial Intelligence in order to model incomplete information. We present a framework for Bilattice-valued Constraint Programming which allows to represent incomplete or conflicting information ...

Large Scale Combinatorial Optimization problems (LSCO) appear in numerous types of industrial applications (e.g. production scheduling, routing problems , nancial applications). They are NP-complete problems characterized by large sets of data, constraints and variables, and often have an impure structure. Tackling such problems successfully requires both experience and skill. The current trend...

Views are a standard abstraction in constraint programming: They make it possible to implement a single version of each constraint, while avoiding to create new variables and constraints that would slow down propagation. Traditional constraint-programming systems provide the concept of variable views which implement a view of the type y = f(x) by delegating all (domain and constraint) operation...

Constraint programming is a relatively new approach for solving combinatorial optimization problems. This approach is especially effective for large scale scheduling problems with side conditions. University course scheduling problem is one of the hard problems in combinatorial optimization. Furthermore, the specific requirements of each institution make it very difficult to suggest a generaliz...

multi objective quadratic fractional programming (moqfp) problem involves optimization of several objective functions in the form of a ratio of numerator and denominator functions which involve both contains linear and quadratic forms with the assumption that the set of feasible solutions is a convex polyhedral with a nite number of extreme points and the denominator part of each of the object...

Recently a logic programming language AC was proposed by Mellarkod et al. (2008) to integrate answer set programming and constraint logic programming. Soon after that, a clingcon language integrating answer set programming and finite domain constraints, as well as an ezcsp language integrating answer set programming and constraint logic programming were introduced. The development of these lang...

In this paper we describe a sound and complete concurrent operational semantics for constraint functional logic programming languages which allows to model declarative applications in which the interaction between demand-driven narrowing and constraint solving helps to prune the search space, leading to shorter goal derivations. We encode concurrency into the generic CFLP(D) scheme, a uniform f...

This paper extends an existing cooperative multi-objective interaction programming problem with interaction constraint for two players or two agents . First, we define an s-optimal joint solution with weight vector to multi-objective interaction programming problem with interaction constraint for two players and get some properties of it. It is proved that the s-optimal joint solution with weig...