Policy improvement methods seek to optimize the parameters of a policy with respect to a utility function. There are two main approaches to performing this optimization: reinforcement learning (RL) and black-box optimization (BBO). In recent years, benchmark comparisons between RL and BBO have been made, and there have been several attempts to specify which approach works best for which types o...

The interest of hybridizing different nature inspired algorithms has been growing in recent years. As a relatively new algorithm in this field, Biogeography Based Optimization(BBO) shows great potential in solving numerical optimization problems and some practical problems like TSP. In this paper, we proposed an algorithm which combines Biogeography Based Optimization (BBO) and Clonal Selection...

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...

Abstract. Proportional-integral-derivative (PID) control is the most popular control architecture used in industrial problems. Many techniques have been proposed to tune the gains for the PID controller. Over the last few years, as an alternative to the conventional mathematical approaches, modern metaheuristics, such as evolutionary computation and swarm intelligence paradigms, have been given...

Biogeography based optimization (BBO) is a new stochastic force based on the science of biogeography. Biogeography is the schoolwork of geographical allotment of biological organisms. BBO utilizes migration operator to share information between the problem solutions. The problem solutions are known as habitats and sharing of features is called migration. In this paper, BBO algorithm is develope...

Differential Evolution (DE) is a fast and robust evolutionary algorithm for global optimization. It has been widely used in many areas. Biogeography-Based Optimization (BBO) is a new biogeography inspired algorithm. It mainly uses the biogeography-based migration operator to share the information among solutions. In this paper, we propose a hybrid DE with BBO, namely DE/BBO, for the global nume...

Image segmentation is an important research issue in image processing. In this paper, hybridizing of the PSO and BBO algorithm for 2-D image segmentation is implemented. The common features from PSO and BBO algorithm are used and then hybridized for the segmentation. The results are evaluated on the basis of parameters; PSNR and SSIM. The results depicts that the proposed hybrid algorithm perfo...

This paper presents a biogeography-based optimization (BBO) algorithm to solve the economic load Dispatch (ELD) problem with generator constraints in thermal plants. Applied method can solve the ELD problem with constraints like transmission losses, ramp rate limits, and prohibited operating zones. Biogeography is the science of the geographical distribution of biological species. The models of...

Biogeography-based optimization (BBO) is a new population-based evolutionary algorithm and one of metaheuristic algorithms. This technique is based on an old mathematical study that explains the geographical distribution of biological organisms. The first original form of BBO was introduced in 2008 and known as a partial migration based BBO. After three months, BBO was re-introduced again with ...

Biogeography based optimization (BBO) is a type of evolutionary algorithm. It is a population based optimization algorithm and provides clarification about the changing distribution of all species in different environment with time. Biogeography-based Optimization (BBO) is a new intelligent optimization algorithm, which was developed by the simulation of the migration of biological organisms on...