Aparameter-free or parameterless bat algorithm is a new variant of the bat algorithmwhich was recently introduced. Characteristic of this algorithm is that user does not need to specify the control parameters when running this algorithm. Thus, this bat algorithm variant can have wide usability in solving real-world optimization problems. In this chapter, a preliminary study of the proposed para...

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probab...

Metaheuristic techniques have been recently used to counter the problems like slow convergence to global minima and network stagnancy in backpropagation neural network (BPNN) algorithm. Previously, a meta-heuristic search algorithm called Bat was proposed to train BPNN to achieve fast convergence in the neural network. Although, Bat-BP algorithm achieved fast convergence but it had a problem of...

Iztok Fister Jr.,∗ Dušan Fister,† and Xin-She Yang‡ Abstract Swarm intelligence is a very powerful technique to be used for optimization purposes. In this paper we present a new swarm intelligence algorithm, based on the bat algorithm. The Bat algorithm is hybridized with differential evolution strategies. Besides showing very promising results of the standard benchmark functions, this hybridiz...

In this paper a multi objective optimal power flow (OPF) is obtained by using BAT search algorithm (BAT) with Unified power flow controller (UPFC). UPFC is a voltage source converter type Flexible Alternating Current Transmission System (FACTS) device. It is able to control the voltage magnitudes, voltage angles and line impedances individually or simultaneously. UPFC along with BAT algorithm i...

In this work, bi-level and multi-level segmentation is proposed for the grey image dataset using a novel Brownian Bat Algorithm (BBA). Maximization of Otsu's between-class variance function is chosen as the objective function. The performance of the proposed CBA is demonstrated by considering five benchmark images and compared with the existing bat algorithms such as Traditional Bat Algori...

Bat algorithm (BA) is one of the most recent bioinspired algorithms. It is based on the echolocation behavior of microbats. The standard BA is proposed only for continuous optimization problems. In this paper, a binary bat algorithm has been developed and implemented to solve the graph coloring problem. To show the feasibility and the effectiveness of the algorithms, we have used the DIMACS ben...

Over fairly recent years the concept of an artificial sport trainer has been proposed in literature. This concept is based on computational intelligence algorithms. In this paper, we try to extend the artificial sports trainer by planning fitness training sessions that are suitable for athletes, especially during idle seasons when no competition takes place (e.g., winter). The bat algorithm was...