Constraint satisfaction has been applied with great success in closed-world scenarios, where all options and constraints are known from the beginning and fixed. With the internet, many of the traditional CSP applications in resource allocation, scheduling and planning pose themselves in open-world settings, where options and constraints must be gathered from different agents in a network. We de...

Symmetry is an important feature in constraint programming. Whilst there has been considerable progress in dealing with symmetry in constraint satisfaction problems, there has been less attention to symmetry in constraint optimization problems. In this paper, we propose some general methods for dealing with symmetry in constraint optimization problems.

We first show that the optimal and undominated outcomes of an unconstrained (and possibly cyclic) CP-net are the solutions of a set of hard constraints. We then propose a new algorithm for finding the optimal outcomes of a constrained CP-net which makes use of hard constraint solving. Unlike previous algorithms, this new algorithm works even with cyclic CP-nets. In addition, the algorithm is no...

Many real-world search and optimization problems naturally involve constraint handling. Recently, quite a few heuristic methods were proposed to solve the nonlinear constrained optimization problems. However, the constraint-handling approaches in these methods have some drawbacks. In this paper, we gave a Multiobjective optimization problem based (MOP-based) formula for constrained single-objec...

Operations research, optimization, constraint programming, hybrid solution methods, decision Handbook of Semidefinite, Cone and Polynomial Optimization:. Learning Outcomes. On successful completion of this module, the student should: Have a working knowledge of the techniques employed in a modern constraint. Constraint-based scheduling: applying constraint programming to scheduling Implementati...

The standard model of distributed constraints optimization problems (DCOPs), assumes that the cost of a constraint is checked by one of the agents involved in the constraint. For DCOPs this is equivalent to the assumption that each constraint has a global cost which applies to each of the participating agents and in other words that all constraints are symmetric. Many multi agent system (MAS) p...

We describe an effective landscape introduced in [1] for the analysis of Constraint Satisfaction problems, such as Sphere Packing, K-SAT and Graph Coloring. This geometric construction reexpresses these problems in the more familiar terms of optimisation in rugged energy landscapes. In particular, it allows one to understand the puzzling fact that unsophisticated programs are successful well be...

We first show that the optimal and undominated outcomes of an unconstrained (and possibly cyclic) CP-net are the solutions of a set of hard constraints. We then propose a new algorithm for finding the optimal outcomes of a constrained CPnet which makes use of hard constraint solving. Unlike previous algorithms, this new algorithm works even with cyclic CP-nets. In addition, the algorithm is not...

My thesis will contribute to the fields of constraint processing and multiagent systems by proposing novel schemes for achieving privacy in constraint optimization as well as new ways of analyzing and understanding the privacy properties of constraint optimization algorithms. Motivation: It is my belief that there are many domains within constraint processing that motivate the need for more pri...