Biogeography based optimization (BBO) and ant colony optimization (ACO) to develop global optimization path. In natural scenario, there are no prior paths and we don't have any prior information about any geographical area. The key factor to achieve a task in such area is Path planning; therefore this research direction is very useful in recent years. This hybrid approach describes autonomous n...

Biogeography-based optimization (BBO) is a population-based evolutionary algorithm (EA) that is based on the mathematics of biogeography. Biogeography is the study of the geographical distribution of biological organisms. In BBO, problem solutions are represented as islands, and the sharing of features between solutions is represented as migration. BBO is similar to a genetic algorithm with glo...

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...

Multiobjective optimization involves minimizing or maximizing multiple objective functions subject to a set of constraints. In this study, a novel constrained multiobjective biogeography optimization algorithm (CMBOA) is proposed. It is the first biogeography optimization algorithm for constrained multiobjective optimization. In CMBOA, a disturbance migration operator is designed to generate di...

Unsupervised data classification (or clustering) analysis is one of the most useful tools and a descriptive task in data mining that seeks to classify homogeneous groups of objects based on similarity and is used in many medical disciplines and various applications. In general, there is no single algorithm that is suitable for all types of data, conditions, and applications. Each algorithm has ...

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 ...

Biogeography Based Optimization (BBO) is a swarm based optimization algorithm that has shown impressive performance over other Evolutionary Algorithms (EAs). Immigration Refusal Biogeography Based Optimization (IRBBO), Enhanced Biogeography Based Optimization (EBBO), Blended Migration are the most improved version of BBO and are known as migration variants of BBO. In this paper, a new concept o...

The main part of the magnetic fluxgate sensor is the magnetic core, the hysteresis characteristic of which affects the performance of the sensor. When the fluxgate sensors are modelled for design purposes, an accurate model of hysteresis characteristic of the cores is necessary to achieve good agreement between modelled and experimental data. The Jiles-Atherton model is simple and can reflect t...