batalgorithm (BA) is a recent optimization algorithm based on swarm intelligence and inspiration from the echolocation behavior of bats. One of the issues in the standard batalgorithm is the premature convergence th...
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batalgorithm (BA) is a recent optimization algorithm based on swarm intelligence and inspiration from the echolocation behavior of bats. One of the issues in the standard batalgorithm is the premature convergence that can occur due to the low exploration ability of the algorithm under some conditions. To overcome this deficiency, directional echolocation is introduced to the standard batalgorithm to enhance its exploration and exploitation capabilities. In addition to such directional echolocation, three other improvements have been embedded into the standard batalgorithm to enhance its performance. The new proposed approach, namely the directional bat algorithm (dBA), has been then tested using several standard and non-standard benchmarks from the CEC'2005 benchmark suite. The performance of dBA has been compared with ten other algorithms and BA variants using non-parametric statistical tests. The statistical test results show the superiority of the directional bat algorithm. (C) 2016 Elsevier Ltd. All rights reserved.
Reliability-based design optimization (RBDO) problems are important in engineering applications, but it is challenging to solve such problems. In this study, a new resolution method based on the directionalbat algori...
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Reliability-based design optimization (RBDO) problems are important in engineering applications, but it is challenging to solve such problems. In this study, a new resolution method based on the directional bat algorithm (dBA) is presented. To overcome the difficulties in the evaluations of probabilistic constraints, the reliable design space concept has been applied to convert the yielded stochastic constrained optimization problem from the RBDO formulation into a deterministic constrained optimization problem. In addition, the epsilon-constraint handling technique has also been introduced to the dBA so that the algorithm can solve constrained optimization problem effectively. The new method has been applied to several engineering problems, and the results show that the new method can solve different varieties of RBDO problems efficiently. In fact, the obtained solutions are consistent with the best results in the literature.
The present study investigates the effect of both ply level material uncertainty and ply angle uncertainty on the failure envelope, strength characteristics and design of laminated composite. Multiple failure envelope...
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The present study investigates the effect of both ply level material uncertainty and ply angle uncertainty on the failure envelope, strength characteristics and design of laminated composite. Multiple failure envelopes and distributions of the strength parameters are obtained for Tsai-Wu and maximum stress criteria using Monte Carlo simulation. A newly developed directional bat algorithm (dBA) is then used to perform the constrained design optimization of laminated composite for the first time while considering uncertainty effects. The effect of ply level uncertainty on failure envelopes and the corresponding optimal design of laminated composite structures is thus quantified.
A novel way of performing nondominated sorting in a multiobjective optimization problem is proposed using a modified directional bat algorithm. Unlike NSGA-II, where the solutions of two generations are merged and the...
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A novel way of performing nondominated sorting in a multiobjective optimization problem is proposed using a modified directional bat algorithm. Unlike NSGA-II, where the solutions of two generations are merged and then sorted for elitism, in the proposed algorithm, the solution is generated and compared with all the previous so-lutions one by one. Hence, this method reduces the computational time by avoiding the comparison of solutions of two generations, at the same time, generates a diverse solution. A unique way of sorting the solutions is proposed using a Nondomination matrix, which can easily be updated if a new solution is accepted. The Non -domination matrix serves as an archiving strategy to preserve elitism. Detailed criteria are proposed for the selection of a new solution. We have tested the proposed algorithm on some of the standard benchmark opti-mization problems. The results show that the proposed algorithm is very competitive and outperforms other algorithms in terms of efficiency and other performance metrics for most problems. The algorithm also provides a standard platform for nondomination sorting, which can be applied to any other metaheuristic algorithm.
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