TECHNISCHE UNIVERSITÄT DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Theoretical Analysis of Diversity Mechanisms for Global Exploration

TECHNISCHE UNIVERSITÄT DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Additive Approximations of Pareto-Optimal Sets by Evolutionary Multi-Objective Algorithms

Often the Pareto front of a multi-objective optimization problem grows exponentially with the problem size. In this case, it is not possible to compute the whole Pareto front efficiently and one is interested in good approximations. We consider how evolutionary algorithms can achieve such approximations by using different diversity mechanisms. We discuss some well-known approaches such as the d...

TECHNISCHE UNIVERSITÄT DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Approximating Minimum Multicuts by Evolutionary Multi-Objective Algorithms

It has been shown that simple evolutionary algorithms are able to solve the minimum cut problem in expected polynomial time when using a multi-objective model of the problem. In this paper, we generalize these ideas to the NP-hard minimum multicut problem. Given a set of k terminal pairs, we prove that evolutionary algorithms in combination with a multi-objective model of the problem are able t...

UNIVERSITY OF DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods A Uni ed Model of Non-Panmictic Population Structures in Evolutionary Algorithms

TECHNISCHE UNIVERSITÄT DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods An Empirical Investigation of Simplified Step-Size Adapatation in Evolution Strategies with a View to Theory

Randomized direct-search methods for the optimization of a function f : R → R given by a black box for f -evaluations are investigated. We consider the cumulative step-size adaptation (CSA) for the variance of multivariate zero-mean normal distributions. Those are commonly used to sample new candidate solutions within metaheuristics, in particular within the CMA Evolution Strategy (CMA-ES), a s...

TECHNISCHE UNIVERSITÄT DORTMUND REIHE COMPUTATIONAL INTELLIGENCE COLLABORATIVE RESEARCH CENTER 531 Design and Management of Complex Technical Processes and Systems by means of Computational Intelligence Methods Analysis of a Simple Evolutionary Algorithm for the Multiobjective Shortest Path Problem

We present a natural fitness function f for the multiobjective shortest path problem, which is a fundamental multiobjective combinatorial optimization problem known to be NP-hard. Thereafter, we conduct a rigorous runtime analysis of a simple evolutionary algorithm (EA) optimizing f . Interestingly, this simple general algorithm is a fully polynomial-time randomized approximation scheme (FPRAS)...