Yet Another Local Search Method for Constraint Solving

Abstract

International audienceWe propose a generic, domain-independent local search method called adaptive search for solving Constraint Satisfaction Problems (CSP). We design a new heuristics that takes advantage of the structure of the problem in terms of constraints and variables and can guide the search more precisely than a global cost function to optimize (such as for instance the number of violated constraints). We also use an adaptive memory in the spirit of Tabu Search in order to prevent stagnation in local minima and loops. This method is generic, can apply to a large class of constraints (e.g. linear and non-linear arithmetic constraints, symbolic constraints, etc) and naturally copes with over-constrained problems. Preliminary results on some classical CSP problems show very encouraging performances.

Targeting the Cell Broadband Engine for constraint‐based local search

“…Such solvers keep an internal representation of variable domains in order to handle all types of constraints. However, during the last decade, the application of LS techniques in the CSP community has started to draw some interest [16,[25][26][27].…”

“…A generic, domain-independent LS method named AS was proposed in [5,26]. AS is a metaheuristic that takes advantage of the structure of the problem to guide the search more precisely than a unique global cost function like the number of violated constraints.…”

Modelling distributed network attacks with constraints

“…AS (Codognet and Diaz, 2001) is a CBLS (Van Hentenryck and Michel, 2005) algorithm, taking into account the structure of the problem and using variable-based information to design general heuristics which help solve the problem. The iterative repairs to the candidate solution in AS are based on variable and constraint error information which seeks to reduce errors on the variables used to model the problem.…”

Using Constraints for Intrusion Detection: The NeMODe System

“…Adaptive Search (AS) [15] is a Constraint Based Local Search [14] algorithm, taking into account the structure of the problem and using variable-based information to design general heuristics which help solve the problem. The iterative repairs to the candidate solution in Adaptive Search are based on variable and constraint error information which seeks to reduce errors on the variables used to model the problem.…”