We introduce the schema bandits algorithm to solve binary combinatorial optimisation problems, like the trap functions and NK landscape, where potential solutions are represented as bit strings. Schema bandits are influenced by two different areas in machine learning, evolutionary computation and multiarmed bandits. The schemata from the schema theorem for genetic algorithms are structured as h...

In [1], Abegaz et. al compared hybrid genetic and evolutionary feature selection (GEFeS) and weighting (GEFeW) on feature sets obtained by Eigenface, LBP, and oLBP feature extraction methods. GEFeS and GEFeW were implemented using a Steady-State Genetic Algorithm (SSGA). In this paper, we extend the work performed in [1] and compared GEFeS and GEFeW implementations using SSGAs and Estimation of...

This article presents a new system for automatically constructing and training radial basis function networks based on original evolutionary computing methods. This system, called Genetic Algorithm Radial Basis Function Networks (GARBFN), is based on two cooperating genetic algorithms. The first algorithm uses a new binary coding, called basic architecture coding, to get the neural architecture...

Binary Decision Diagram (BDD) is a data structure proved to be compact in representation and efficient in manipulation of Boolean formulas. Using Binary decision diagram in network reliability analysis has already been investigated by some researchers. In this paper we show how an exact algorithm for network reliability can be improved and implemented efficiently by using CUDD - Colorado Univer...

A multimodal problem generator was used to test three versions of genetic algorithm and the binary particle swarm algorithm in a factorial time-series experiment. Specific strengths and weaknesses of the various algorithms were identified.

Abstract Tree-based classifiers are important in pattern recognition and have been well studied. Although the problem of finding an optimal decision tree has received attention, it is a hard optimization problem. Here we propose utilizing a genetic algorithm to improve on the finding of compact, near-optimal decision trees. We present a method to encode and decode a decision tree to and from a ...

Quantum-behaved particle swarm optimization (QPSO) algorithm is a variant of the traditional particle swarm optimization (PSO). The QPSO that was originally developed for continuous search spaces outperforms the traditional PSO in search ability. This paper analyzes the main factors that impact the search ability of QPSO and converts the particle movement formula to the mutation condition by in...

a gyroscope is a device for measuring or maintaining orientation , based on the principles of conservation of angular momentum . the device is a spinning wheel or disk whose axle is free to take any orientation. this orientation changes much less in response to a given external torque than it would without the large angular momentum associated with the gyroscope's high rate of spin. since exter...

The compact genetic algorithm is an Estimation of Distribution Algorithm for binary optimisation problems. Unlike the standard Genetic Algorithm, no cross-over or mutation is involved. Instead, the compact Genetic Algorithm uses a virtual population represented as a probability distribution over the set of binary strings. At each optimisation iteration, exactly two individuals are generated by ...