The set covering problem (SCP) is a wellknown combinatorial optimization problem. We present a GRASP algorithm to Unicost Set Covering Problem, a special case of the Set Covering Problem where no distinction is made between covering sets. The most significant contribution of the algorithm is the incorporation of a local improvement procedure based on the heuristics to solve satisfiability probl...

nowadays, different methods are used to solve optimization problems which ,one of the newest is bco method that are inspired by the nature and derived from the social life of bees of these methods can be noted that bco is derived from the social life of bees. we use in this paper fuzzy logic for bee‟s decision stage. at the end, we solve two different problem that have already been solved by es...

We present a new approach to automatic test pattern generation for very large scale integrated sequential circuit testing. This approach is more eecient than past test generation methods, since it exploits knowledge of potential circuit defects. Our method motivates a new combinatorial optimization problem, the Tour Covering Problem. We develop heuristics to solve this optimization problem, the...

Many optimization techniques have been proposed since the inception of engineering optimization in 1960s. Traditional mathematical modeling-based approaches are incompetent to solve the engineering optimization problems, as these problems have complex system that involves large number of design variables as well as equality or inequality constraints. In order to overcome the various difficultie...

many real world problems can be modelled as an optimization problem. evolutionary algorithms are used to solve these problems. ant colony algorithm is a class of evolutionary algorithms that have been inspired of some specific ants looking for food in the nature. these ants leave trail pheromone on the ground to mark good ways that can be followed by other members of the group. ant colony optim...