In the last 20 years, evolutionary algorithms (EAs) have shown to be an effective method to
solve multiobjective optimization problems (MOPs). Due to their population-based nature …

Problems with multiple objectives arise in a natural fashion in most disciplines and their
solution has been a challenge to researchers for a long time. Despite the considerable …

A general review of game-theory based evolutionary algorithms (EAs) is presented in this
study. Nash equilibrium, Stackelberg game and Pareto optimality are considered, as game …

In addition to the need for satisfying several competing objectives, many real-world
applications are also dynamic and require the optimization algorithm to track the changing …

Node-link diagrams are widely used to facilitate network explorations. However, when using
a graph drawing technique to visualize networks, users often need to tune different algorithm …

Using different methods for laying out a graph can lead to very different visual appearances,
with which the viewer perceives different information. Selecting a “good” layout method is …

Many real-world problems involve the simultaneous optimization of several competing
objectives and constraints that are difficult, if not impossible, to solve without the aid of …

This paper proposes an interactive multiobjective evolutionary algorithm (MOEA) that
attempts to learn a value function capturing the users' true preferences. At regular intervals …

Different layouts can characterize different aspects of the same graph. Finding a “good”
layout of a graph is thus an important task for graph visualization. In practice, users often …

The following paper describes a cooperative coevolutionary algorithm which incorporates a
novel collaboration formation mechanism. It encourages rewarding of components …