UDGVNS
Team CODAG
Solve large combinatorial optimization problems by efficiently exploiting tree decomposition within a variable neighborhood search. The UDGVNS method takes as input a problem defined by a set of variables where each variable is associated with a finite set of possible values. These variables are subject to soft constraints modeled as cost functions. Each cost function gives the weight of violation of an assignment for a given constraint. The more the assignment of the variables violates the constraints, the higher the cost will be. The objective is to find an assignment of all variables that minimizes the sum of the cost functions, ideally a cost equal to zero.
Contributor
Abdelkader Ouali