Adaptive Search is a generic, domain-independent constraint-based Local Search method.
This metaheuristic takes advantage of the structure of the problem in terms of constraints and variables in order to guide the search.

The input of the method is a CSP, defined as a triple (X;D;C), where X is a set of variables, D is a set of domains (i.e., finite sets of possible values for each variable), and C a set of constraints restricting the values that the variables can simultaneously take.
For each constraint, an error function needs to be defined:
it gives, for each tuple of variable values (i.e., a variable assignment), an indication on how much the constraint is violated.
The algorithm also uses a short-term adaptive memory in the spirit of Tabu Search to avoid stagnation in local minima and loops.

This archive contains the source code of sequential and parallel versions of the Adaptive Search algorithm and its specialization on several examples.

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