The Wind Driven Optimization Technique and its Application in Electromagnetics

Bayraktar, Zikri; Kömürcü, Müge; Bossard, Jeremy A.; Werner, Douglas H.

doi:10.1109/tap.2013.2238654

Cited by 286 publications

(142 citation statements)

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“…In the second test instance, UCAV starts at (10,15) and finishes at (80,75). In this battlefield environment, there are eight threat centers.…”

Section: Resultsmentioning

confidence: 99%

“…Tables 1-7 represent the necessary parameters used for QWDO, QBA, QPSO, WDO, BA, PSO and DE algorithms, respectively. Bayraktar et al did a lot of research for the parameters setting of WDO algorithm [10]. The parameters for the set of quantum algorithms are the same as the original algorithm.…”

Section: Parameters Settingmentioning

confidence: 99%

“…The wind driven optimization (WDO) is a novel nature-inspired technique that was proposed by Bayraktar et al in 2010 [9,10]. In the atmosphere, wind balances atmospheric pressure through flow.…”

Section: Introductionmentioning

confidence: 99%

“…It is easy for the WDO algorithm to fall into a local optimal solution in the early stage of solving an optimization problem, which will lead to the loss of diversity of population [10]. In order to overcome this shortcoming, we apply the quantum encoding theory to the WDO algorithm, and propose a new algorithm called quantum wind driven optimization (QWDO).…”

Section: Introductionmentioning

confidence: 99%

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Quantum Wind Driven Optimization for Unmanned Combat Air Vehicle Path Planning

et al. 2015

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Unmanned combat air vehicle (UCAV) path planning aims to calculate the optimal or suboptimal flight path considering the different threats and constraints under the complex battlefield environment. This flight path can help the UCAV avoid enemy threats and improve the efficiency of the investigation. This paper presents a new quantum wind driven optimization (QWDO) for the path planning of UCAV. QWDO algorithm uses quantum rotation gate strategy on population evolution and the quantum non-gate strategy to realize the individual variation of population. These operations improve the diversity of population and avoid premature convergence. This paper tests this optimization in two instances. The experimental results show that the proposed algorithm is feasible in these two cases. Compared to quantum bat algorithm (QBA), quantum particle swarm optimization (QPSO), wind driven optimization (WDO), bat algorithm (BA), particle swarm optimization (PSO), and differential evolution (DE), the QWDO algorithm exhibited better performance. The simulation results demonstrate that the QWDO algorithm is an effective and feasible method for solving UCAV path planning.Keywords: wind driven optimization (WDO); unmanned combat air vehicle (UCAV); path planning; quantum wind driven optimization (QWDO) OPEN ACCESSAppl. Sci. 2015Sci. , 5 1458

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“…In the second test instance, UCAV starts at (10,15) and finishes at (80,75). In this battlefield environment, there are eight threat centers.…”

Section: Resultsmentioning

confidence: 99%

Section: Parameters Settingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Quantum Wind Driven Optimization for Unmanned Combat Air Vehicle Path Planning

et al. 2015

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“…GA is inspired by natural process of evolution present in living organisms invented by Holland. It has been applied to various optimization problems [20]. The Wind Driven Optimization (WDO) technique is one of the latest nature inspired optimization technique [21].…”

Section: Tools and Techniquesmentioning

confidence: 99%