We present a robust set of features that analyze the fitness landscape of black-box optimization (BBO) problems. We show that these features are effective for training a portfolio algorithm using Instance Specific Algorithm Configuration (ISAC). BBO problems arise in numerous applications, especially in scientific and engineering contexts. BBO problems are characterized by computationally inten...

The present paper proposes the development of a three-level thresholding based image segmentation technique for real images obtained from CT scanning of a human head. The proposed method utilizes maximization of fuzzy entropy to determine the optimal thresholds. The optimization problem is solved by employing a very recently proposed population-based optimization technique, called biogeography ...

Biogeography-based optimization (BBO) has recently become popular in unmanned aerial vehicle (UAV) path planning. Similar to other evolutionary algorithms, the performance of BBO is affected when the parameter setting is not finely tuned. Therefore, the BBO parameters are optimized in this research particularly for application in UAV path planning. Each combination setting of parameters is simu...

In this article, we report how the growth method used for barium beta-borate β−BaB2O4 (BBO) impacts its high power second harmonic generation properties in the deep-UV. We compared a BBO crystal grown by flux (Top Seeded Solution Growth or TSSG) and a BBO crystal grown by the Czochralski (CZ) method. We first characterized their transparency properties, then we measured their single-pass second...

Biogeography-based optimization (BBO) is a new population-based evolutionary algorithm and one of meta-heuristic 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. Few months later, BBO was re-introduced again with a...

Biogeography-based optimization (BBO) is an evolutionary algorithm (EA) based upon the models of biogeography, which describe the relationship between habitat suitability and the migration of species across habitats. In this work, we apply BBO to the problem of tuning the fuzzy tracking controller of mobile robots. This is an extension of previous work, in which we used BBO to tune a proportion...

Complex systems are frequently found in modern industry. But with their multisubsystems, multiobjectives, and multiconstraints, the optimization of complex systems is extremely hard. In this paper, a new algorithm adapted from biogeography-based optimization (BBO) is introduced for complex systemoptimization. BBO/Complex is the combination of BBOwith amultiobjective ranking system, an innovativ...

Biogeography-based optimization (BBO) is a relatively new bioinspired heuristic for global optimization based on the mathematical models of biogeography. By investigating the applicability and performance of BBO for integer programming, we find that the original BBO algorithm does not perform well on a set of benchmark integer programming problems. Thus we modify the mutation operator and/or th...

The main challenge with particle filtering is particle degeneracy and the accurate estimation cannot be achieved generally because of serious impoverishment problem, although resampling operation could solve degeneracy to a certain extent. In this paper, we propose an improved particle filtering approach based on biogeography-based optimization (BBO) algorithm, called BBO-PF, for state estimati...

Biogeography-based optimization (BBO) algorithm is a new kind of optimization technique based on biogeography concept. This population-based algorithm uses the idea of the migration strategy of animals or other species for solving optimization problems. In this paper, the BBO algorithm is developed for flexible job shop scheduling problem (FJSP). It means that migration operators of BBO are dev...