Bounding the Optimum of Constraint Optimization Problems

  title={Bounding the Optimum of Constraint Optimization Problems},
  author={Simon de Givry and G{\'e}rard Verfaillie and T. Schiex},
Solving constraint optimization problems is computationally so expensive that it is often impossible to provide a guaranteed optimal solution, either when the problem is too large, or when time is bounded. In these cases, local search algorithms usually provide good solutions. However, and even if an optimality proof is unreachable, it is often desirable to have some guarantee on the quality of the solution found, in order to decide if it is worthwile to spend more time on the problem. This… 

Anytime Lower Bounds for Constraint Violation Minimization Problems

It is shown that a new algorithm, resulting from a combination of the Russian Doll Search and Iterative Deepening algorithms, clearly outperforms five known algorithms and allows high lower bounds to be rapidly produced.

Optimization Methods for Constraint Resource Problems

A tight lower bound of the problem optimum is obtained by adding redundant constraints that take into account the "wastage" in a partial solution by using resource optimization methods for solving efficiently synthesis problems in a constraint-based framework.

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Abstracting soft constraints: Framework, properties, examples

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Up and Down Mini-Buckets : A Scheme for Approximating Combinatorial Optimization Tasks Tracking number : 708

UD-MB is presented, a new algorithm that applies the mini-bucket elimination idea to accomplish the problem of computing lower bounds on the optimal costs associated with each unary assignment of a value to a variable in combinatorial optimization problems.

Arc consistency for soft constraints



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The Russian Doll Search algorithm is introduced, which replaces one search by n successive searches on nested subproblems, records the results of each search and uses them later, when solving larger subpro problems, in order to improve the lower bound on the global valuation of any partial assignment.

Analysis of Heuristic Methods for Partial Constraint Satisfaction Problems

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An Optimal Admissible Tree Search

This heuristic depth-first iteratiw-deepening algorithm is the only known algorithm that is capable of finding optimal solutions to randomly generated instances of the Fifeen Puzzle within practical resource limits.

Directed Arc Consistency Preprocessing

  • R. Wallace
  • Computer Science
    Constraint Processing, Selected Papers
  • 1995
This work describes a family of strategies based on directed arc consistency testing during preprocessing that retain the benefits of full arc consistency checking, while improving lower bound calculations.

Partial Constraint Satisfaction

Local Search in Combinatorial Optimisation.

This book is an important reference volume and an invaluable source of inspiration for advanced students and researchers in discrete mathematics, computer science, operations research, industrial engineering and management science.

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Nogood recording for valued constraint satisfaction problems

  • Pierre DagoG. Verfaillie
  • Computer Science
    Proceedings Eighth IEEE International Conference on Tools with Artificial Intelligence
  • 1996
This study aims to use Nogood Recording in the wider scope of the Valued CSP framework (VCSP) to enhance the branch and bound algorithm and uses nogoods to increase the lower bound used by the branches and bound to prune the search.