The congestion is the most important issue that effects on performance of data transition over internet networks. One techniques developed active queue management (AQM) prepares an efficient control by reducing losing packets, size, and energy consumption. Therefore, AQM technique deemed as a base many algorithms schemes. This work suggested using proportional integral (PI) controller then use ...

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). Whereas BBO algorithms are generic optimization methods that, due to there generality, may also be applied to optimizing policy parameters, RL algorithms are specifi...

Automotive system optimization problems are difficult to solve with traditional optimization techniques because the optimization problems are complex, and the simulations are computationally expensive. These two characteristics motivate the use of evolutionary algorithms and meta-modeling techniques respectively. In this work, we apply biogeography-based optimization (BBO) to radial basis funct...

Independent component analysis (ICA) is a signal processing technique that can be used to extract meaningful components from a dataset. Biogeography based optimization (BBO) algorithm is a recently developed stochastic optimization algorithm. In this paper, we report the use of the BBO algorithm to optimize a contrast function that measures the statistical independence of the recovered componen...

Hybridization in optimization methods plays a very vital role to make it effective and efficient. Different optimizationmethods have different search tendency and it is always required to experiment the effect of hybridizing different search tendency of the optimization algorithmwith each other. This paper presents the effect of hybridizing Biogeography-BasedOptimization (BBO) techniquewith Art...

Motivated by the migration mechanisms of ecosystems, various extensions to biogeography-based optimization (BBO) are proposed here. As a global optimization method, BBO is an original algorithm based on the mathematical model of organism distribution in biological systems. BBO is an evolutionary process that achieves information sharing by biogeography-based migration operators. In BBO, habitat...

Biogeography-based optimization (BBO) is a new evolutionary optimization method that is based on the science of biogeography. We propose two extensions to BBO. First, we propose a blended migration operator. Benchmark results show that blended BRO outperforms standard BBO. Second, we employ blended BRO to solve constrained optimization problems. Constraints are handled by modifying the BRO immi...

Biogeography-based optimization (BBO) is a new population-based evolutionary algorithm and is based on an old theory of island biogeography that explains the geographical distribution of biological organisms. BBO was introduced in 2008 and then a lot of modifications and hybridizations were employed to enhance its performance. The researchers found that the original version of BBO has some weak...

this paper presents a biogeography-based optimization (bbo) algorithm to solve the economic loaddispatch (eld) problem with generator constraints in thermal plants. the applied method can solvethe eld problem with constraints like transmission losses, ramp rate limits, and prohibited operatingzones. biogeography is the science of the geographical distribution of biological species. the modelsof...

We show that the Big Bang Observer (BBO), a proposed space-based gravitational-wave (GW) detector, would provide ultra-precise measurements of cosmological parameters. By detecting ∼ 3 × 10 compact-star binaries, and utilizing them as standard sirens, BBO would determine the Hubble constant to ∼ 0.1%, and the dark energy parameters w0 and wa to ∼ 0.01 and ∼ 0.1, respectively. BBO’s dark-energy ...