The efficiency of any metaheuristic algorithm largely depends on the way of balancing local intensive exploitation and global diverse exploration. Studies show that bat algorithm can provide a good balance between these two key components with superior efficiency. In this paper, we first review some commonly used metaheuristic algorithms, and then compare the performance of bat algorithm with t...

Bat algorithm (BA) is a novel stochastic global optimization algorithm. Cloud model is an effective tool in transforming between qualitative concepts and their quantitative representation. Based on the bat echolocation mechanism and excellent characteristics of cloud model on uncertainty knowledge representation, a new cloud model bat algorithm (CBA) is proposed. This paper focuses on remodelin...

Clustering is one of the data analysis methods that are widely used in data mining. In this method, we partitioned the data into different subset which is known as cluster. Cluster analysis is the data reduction toll for classifying a “mountain‟ of information into manageable meaningful piles. This method is vast research area in the field of data mining. In this paper, a partitioning clusterin...

This paper presents a new metaheuristic algorithm called BAT search Algorithm (BAT). The BAT search algorithm is used to solve Optimal Power Flow (OPF) problem with the Thyristor Controlled Series Capacitor (TCSC). The TCSC is used to reduce the transmission line losses and improve the voltage profile of the power system. The effectiveness of the BAT Algorithm has been tested for various bus sy...

A new metaheuristic method, the BAT search algorithm based on the echolocation behaviour of bats is proposed in this paper for optimal design of Power System Stabilizers (PSSs) in a multimachine environment. The PSSs parameter tuning problem is converted to an optimization problem which is solved by BAT search Algorithm. An eigenvalues based objective function involving the damping factor, and ...

The various meta-heuristic techniques for cloud and grid environment are: Ant Colony Optimization (ACO), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Tabu Search, Firefly Algorithm, BAT Algorithm and many more. So this paper represents the two types of meta-heuristic techniques, i.e. BAT algorithm and Genetic Algorithm. The different types of methods which comprise meta-heuristic ...

Economic dispatch is an important non-linear optimization task in power systems. In this process, the total power demand is distributed amongst the generating units such that each unit satisfies its generation limit constraints and the cost of power production is minimized. This paper presents an over view of three optimization algorithms namely real coded genetic algorithm, particle swarm opti...

This paper investigates the multistage hybrid flow shop (HFS) scheduling problems using the new bat algorithm. A HFS is the generalisation of flowshop with multiple machines. HFS is one of the important scheduling problems that represent many industries like iron and steel, chemical, textile and ceramic industries. The HFS scheduling problems have been proved to be NP-hard. A recently developed...