Kazuhiro Ohkura

A symbiotic evolutionary algorithm for dynamic facility layout problem

A symbiotic evolutionary algorithm (SymEA) for dynamic facility layout problem (DFLP) is developed and tested. SymEA differs from the existing EA approaches for DFLP in two ways: first, it adopted a coevolutionary multi-population approach, second, the generational replacement strategy (/spl mu/, /spl lambda/)-selection of evolution strategies is used to refine the symbiotic relationship.

Robust Swarm Robotics System Using CMA-NeuroES with IncrementalEvolution

Swarm robotics (SR) is a novel approach to the coordination of large numbers of homogeneous robots; SR takes inspiration from social insects. Each individual robot in an SR system (SRS) is relatively simple and physically embodied. Researchers aim to design robust, scalable, and flexible collective behaviours through local interactions between robots and their environment. In this study, a simulated robot controller evolved by a recurrent artificial neural network with the covariance matrix adaptation evolution strategy, i.e., CMANeuroES is adopted for incremental artificial evolution. Cooperative food foraging is conducted by our proposed controller as one of the most complex simulation applications. Since a high level of robustness is expected in an SRS, several tests are conducted to verify that incremental artificial evolution with CMANeuroES generates the most robust robot controller among the ones tested in simulation experiments.

Evolutionary dynamics of genetic algorithm in the fitness landscape including neutral Networks.

Neutral networks, which are landscapes containing neighboring points of equal fitness, have attracted much research interest in recent years. In this paper, we conduct a series of computer simulations to investigate the effect of an error threshold on the moving speed of a population as well as a variable mutation rate strategy against ruggedness. Two kinds of GA are adopted. One is the simple GA where the mutation rate is constant, and the other is the operon-GA whose effective mutation rate is changing at each locus independently according to the history of the genetic search. The results demonstrate that the moving speed of a population is correlated with the selection pressure as well as the mutation rate. The variable mutation rate strategy is beneficial in the cases of the simplest test function and complex test functions. This tendency becomes clearer with the increase of ruggedness in the test functions.