Understanding the search dynamics of multiobjective evolutionary algorithms (MOEAs) is still an open problem. This paper extends a recent network-based tool, trajectory networks (STNs), to model behavior MOEAs. Our approach uses idea decomposition, where problem transformed into several single-objective problems. We show that STNs can be used and distinguish two popular algorithms, MOEA/D NSGA-...

being one of the major research fields in the robotics discipline, the robot motion planning problem deals with finding an obstacle-free start-to-goal path for a robot navigating among workspace obstacles. such a problem is also encountered in path planning of intelligent vehicles and automatic guided vehicles (agvs). traditional (exact) algorithms have failed to solve the problem effectively s...

E VOLUTIONARY computation methods, such as evolutionary algorithms or swarm intelligence algorithms, have been successfully applied to a wide range of difficult problems. These include classical NP-hard combinatorial optimization problems and a variety of hard real-world optimization problems. Real-world problems, in particular, are difficult to solve using traditional search methods because of...

In this paper we analyze the application of the Ant Colony Optimization to the Minimum Weight Vertex Covering Problem. We use the software system that we developed and implemented different standard ACO algorithms to this problem: Ant Colony System, the use of Elitism, Rank based approach and the MinMax system. We have made a comparative assessment of the effectiveness of these algorithms to th...