Search algorithms for solving CSP (Constraint Satisfaction Problems) usually fall into one of two main families: local search algorithms and systematic algorithms. Both families have their advantages. Designing hybrid approaches seems promising since those advantages may be combined into a single approach. In this paper, we present a new hybrid technique. It performs a local search over partial assignments instead of complete assignments, and uses filtering techniques and conflict-based techniques to efficiently guide the search. This new technique benefits from both classical approaches: aprioripruning of the search space from filtering-based search and possible repair of early mistakes from local search. We focus on a specific version of this technique: tabu decision-repair.Experiments done on open-shop scheduling problems show that our approach competes well with the best highly specialized algorithms. 2002 Elsevier Science B.V. All rights reserved.

Most of complete search algorithms over Constraint Satisfaction Problems (csp) are based on Standard Backtracking. Two main

. In the last twenty years, many algorithms and heuristics were developed to find solutions in constraint networks. Their number increased to such an extent that it quickly became necessary to compare their performances in order to propose a small number of "good" methods. These comparisons often led us to consider FC or FC-CBJ associated with a "minimum domain" variable ordering heuristic as the best techniques to solve a wide variety of constraint networks. In this paper, we first try to convince once and for all the CSP community that MAC is not only more efficient than FC to solve large practical problems, but it is also really more efficient than FC on hard and large random problems. Afterwards, we introduce an original and efficient way to combine variable ordering heuristics. Finally, we conjecture that when a good variable ordering heuristic is used, CBJ becomes an expensive gadget which almost always slows down the search, even if it saves a few constraint checks. 1 Introducti...

In recent years, many improvements to backtracking algorithms for solving constraint satisfaction problems have been proposed. The techniques for improving backtracking algorithms can be conveniently classified as look-ahead schemes and look-back schemes. Unfortunately, look-ahead and look-back schemes are not entirely orthogonal as it has been observed empirically that the enhancement of look-ahead techniques is sometimes counter-productive to the effects of look-back techniques. In this paper, we focus on the relationship between the two most important look-ahead techniques -- using a variable ordering heuristic and maintaining a level of local consistency during the backtracking search -- and the look-back technique of conflict-directed backjumping (CBJ). We show that there exists a "perfect" dynamic variable ordering such that CBJ becomes redundant. We also show theoretically that as the level of local consistency that is maintained in the backtracking search is increased, the less that backjumping will be an improvement. Our theoretical results partially explain why a backtracking algorithm doing more in the look-ahead phase cannot benefit more from the backjumping look-back scheme. Finally, we show empirically that adding CBJ to a backtracking algorithm that maintains generalized arc consistency (GAC), an algorithm that we refer to as GAC-CBJ, can still provide orders of magnitude speedups. Our empirical results contrast with Bessiere and Regin's conclusion (1996) that CBJ is useless to an algorithm that maintains arc consistency.

In this paper, we present a general algorithm which gives an uniform view of several state-of-the-art systematic backtracking search algorithms for solving both binary and nonbinary CSP instances. More precisely, this algorithm integrates the most usual or/and sophisticated look-back and look-ahead schemes. By means of this algorithm, our purpose is then to study the interest of backjump-based techniques with respect to conflict-directed variable ordering heuristics. 1

In this paper, we study two recently presented algorithms employing a "full look-ahead" strategy: MAC (Maintaining Arc Consistency); and the hybrid MAC-CBJ, which combines conflict-directed backjumping capability with MAC. We observe their behaviour with respect to the phase transition properties of randomly-generated binary constraint satisfaction problems, and investigate the benefits of maintaining a higher level of consistency during search by comparing MAC and MAC-CBJ with the FC and FC-CBJ algorithms, which maintain only node consistency. The phase transition behaviour that has been observed for many classes of problem as a control parameter is varied has prompted a flurry of research activity in recent years. Studies of these transitions, from regions where most problems are easy and soluble to regions where most are easy but insoluble, have raised a number of important issues such as the phenomenon of exceptionally hard problems ("ehps") in the easy-soluble region, and the grow...

In this paper, a new search technique over numeric csps is presented: dynamic domain splitting. The usual search technique over numeric csps is a dichotomic search interleaved with a consistency filtering, which is called domain splitting. This paper proposes to replace chronological backtracking at the core of domain splitting by a non destructive backtracking technique.

This paper presents a set of tools based on explanations for constraint programming. These tools exploit k-relevant explanations which enable us to use several explanations, which can sometimes leads to better diagnosis. k-relevant explanations are introduced and used to provide: diagnosis tools (state analysis, contradiction analysis, constraint impact analysis), interaction tools (dynamic constraint addition/retraction simulation), as well as improved search techniques.

Recent works on constraint relaxation [Jussien, 1997; Jussien and Boizumault, 1997b] provided the decorum system (Deduction-based Constraint Relaxation Management). That system can be seen as an integration of arc-consistency within the dynamic backtracking algorithm [Ginsberg, 1993]. Dynamic backtracking replaces the backtracking process by a much less blind behavior that consists in local modifications of the choices made up to the current situation. In this paper, a new enumeration technique over numeric csps is proposed: dynamic domain splitting. This is a domain splitting search where chronological backtracking is replaced by a kind of dynamic backtracking.

We report an investigation into how constraint solving techniques can be used to search for patterns in sequences (or strings) of symbols over a finite alphabet. We define a constraint-based structure description language for biosequences, and give the definition of an algorithm to solve the structure searching problem as a CSP. The methodology which we have developed is able to describe two-dimensional structure of biosequences, such as tandem repeats, stem loops, palindromes and pseudo-knots. We also report on an implementation of the language in the constraint logic programming language clp(FD), with test results of a simple searching algorithm, and results from a preliminary implementation in C++ using consistency checking techniques from solving CSP. Keywords: constraints, biostructures, description language, searching. 1 Introduction The aim of the work described in this paper is to use constraint solving techniques to search for structural patterns in sequences (or st...