In this paper a new optimization algorithm, the biogeography based optimization (BBO) is employed to design a robust power oscillation damping (POD) controller using unified power flow controller (UPFC). The controller that is used to damp low frequency oscillation is designed over a wide range of operating points using two different objective functions. The obtained controllers are then verifi...

Abstract: “Mixels” are usually the biggest reason for degrading the image quality especially for remote sensing or satellites images. In this paper we present an approach for resolving the mixed pixels by using optimization algorithm i.e. Biogeography based optimization and genetic algorithm. The hybrid approach is used for resolving super pixel problem. This paper deals with the comparison of ...

A new hybrid Optimization Algorithm is proposed to solve Constrained Multi-objective Optimization Problems (CMOPs). The algorithm is named BBO/DE which combines the exploitation ability of Biogeography-based Optimization (BBO) and the exploration ability of Differential Evolution (DE). Meanwhile distance measures and adaptive penalty functions are adopted to handle the constraints so that optim...

Hybrid evolutionary algorithms (EAs) are effective optimization methods that combine multiple EAs. We propose several hybrid EAs by combining some recently-developed EAs with a biogeography-based hybridization strategy. We test our hybrid EAs on the continuous optimization benchmarks from the 2013 Congress on Evolutionary Computation (CEC) and on some real-world traveling salesman problems. The...

Biogeography is the study of the geographical distribution of biological organisms. The mindset of the engineer is that we can learn from nature. Biogeography Based Optimization is a burgeoning nature inspired technique to find the optimal solution of the problem. Satellite image classification is an important task because it is the only way we can know about the land cover map of inaccessible ...

From last two decades many optimization techniques have been evolved. PSO and BBO are the two techniques that have been widely used in Swarm Optimization. PSO is better than many genetic algorithms. PSO has applications in various areas like Optimization, Neural Networks training, Fuzzy controls and etc. BBO is based on science of biogeography. BBO has some features common to PSO and Genetic al...