Development of a Parallel BAT and Its Applications in Binary-state Network Reliability Problems

Various networks are broadly and deeply applied in real-life applications. Reliability is the most important index for measuring the performance of all network types. Among the various algorithms, only implicit enumeration algorithms, such as depth-first-search, breadth-search-first, universal generating function methodology, binary-decision diagram, and binary-addition-tree algorithm (BAT), can be used to calculate the exact network reliability. However, implicit enumeration algorithms can only be used to solve small-scale network reliability problems. The BAT was recently proposed as a simple, fast, easy-to-code, and flexible make-to-fit exact-solution algorithm. Based on the experimental results, the BAT and its variants outperformed other implicit enumeration algorithms. Hence, to overcome the above-mentioned obstacle as a result of the size problem, a new parallel BAT (PBAT) was proposed to improve the BAT based on compute multithread architecture to calculate the binary-state network reliability problem, which is fundamental for all types of network reliability problems. From the analysis of the time complexity and experiments conducted on 20 benchmarks of binary-state network reliability problems, PBAT was able to efficiently solve medium-scale network reliability problems

Optimasi Penampang Bambu Pada Struktur Rangka Batang Bidang Dengan Menggunakan Binary Bat Algorithm

Bambu merupakan salah satu material bangunan yang ramah lingkungan dan termasuk dalam kategori material yang berkelanjutan (sustainable material) dan banyak digunakan dalam konstruksi sipil khususnya bangunan, akan tetapi kegunaan bambu pada kontruksi bangunan biasanya hanya sebatas sebagai perancah saja. Pada penelitian ini, bambu akan diaplikasikan sebagai material pada struktur rangka atap dari bangunan yang direpresentasikan oleh struktur rangka batang bidang. Terdapat dua jenis rangka batang bidang yang akan digunakan, yaitu struktur rangka batang bidang dengan 10 batang (benchmark problem) dan tipe howe dengan 13 batang. Ukuran penampang dari masing-masing batang dioptimasikan guna mendapatkan hasil yang optimum dari segi berat keseluruhan struktur. Binary bat algorithm digunakan sebagai tools untuk mengoptimasi ukuran penampang dari elemen struktur rangka batang bidang tersebut. Berdasarkan hasil yang didapatkan, binary bat algorithm mampu mendapatkan ukuran penampang yang optimum untuk masing-masing batang baik untuk struktur rangka batang bidang dengan 10 batang dan struktur rangka batang bidang tipe howe

Bat Algorithm: Literature Review and Applications

Bat algorithm (BA) is a bio-inspired algorithm developed by Yang in 2010 and BA has been found to be very efficient. As a result, the literature has expanded significantly in the last 3 years. This paper provides a timely review of the bat algorithm and its new variants. A wide range of diverse applications and case studies are also reviewed and summarized briefly here. Further research topics are also discussed.Comment: 10 page

An effective beamformer for interference suppression without knowing the direction

This paper proposes an effective beamformer for uniform linear arrays of half-wave dipole antennas based on binary bat algorithm (BBA) by controlling complex weights (both amplitudes and phases) excited at elements in an array. The proposed beamformer can impose adaptive nulls at interferences without knowing directions in the sidelobe region by minimizing the total output power of an array, whereas the main lobe and sidelobe levels are maintained. To demonstrate this capability, the proposal will be evaluated in several scenarios, compared to a beamformer based on binary particle swarm optimization (BPSO)

The performance of Taguchi’s T-method with binary bat algorithm based on great value priority binarization for prediction

Taguchi’s T-method is a predictive modeling technique under the Mahalanobis-Taguchi system that is based on the regression principle and robust quality engineering elements to predict future state or unknown outcomes. In enhancing prediction accuracy, the T-method employed Taguchi’s orthogonal array as a variable selection approach to determine a subset of independent variables that are significant toward the dependent variable or output. This, however, leads to sub-optimality of prediction accuracy as the orthogonal array design lacks in offering higher-order variable interactions, in addition to its fixed and limited variable combinations to be assessed and evaluated. This paper proposes an optimization algorithm based on the Binary Bat algorithm methodology for replacing the conventional orthogonal array approach. Specifically, a Great Value Priority binarization scheme is employed to transform the continuous location of the bat into a binary bit, representing a combination of the variable in binary string form. A comparative study was conducted, and the mean absolute error metric was used as the performance measure. Experiments show that the T-method prediction accuracy with the Binary Bat algorithm based on the Great Value Priority binarization scheme is better than that of the conventional T-method-orthogonal array

Entanglement Increases the Error-Correcting Ability of Quantum Error-Correcting Codes

If entanglement is available, the error-correcting ability of quantum codes can be increased. We show how to optimize the minimum distance of an entanglement-assisted quantum error-correcting (EAQEC) code, obtained by adding ebits to a standard quantum error-correcting code, over different encoding operators. By this encoding optimization procedure, we found several new EAQEC codes, including a family of [[n, 1, n; n-1]] EAQEC codes for n odd and code parameters [[7, 1, 5; 2]], [[7, 1, 5; 3]], [[9, 1, 7; 4]], [[9, 1, 7; 5]], which saturate the quantum singleton bound for EAQEC codes. A random search algorithm for the encoding optimization procedure is also proposed.Comment: 39 pages, 10 table