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A Hybrid Algorithm Based on Invasive Weed Optimization Algorithm and Grey Wolf Optimization Algorithm

机译:一种基于侵入性杂草优化算法和灰狼优化算法的混合算法

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In this research, two algorithms first, considered to be one of hybrid algorithms. And it is algorithm represents invasive weed optimization. This algorithm is a random numerical algorithm and the second algorithm representing the grey wolves optimization. This algorithm is one of the algorithms of swarm intelligence in intelligent optimization. The algorithm of invasive weed optimization is inspired by nature as the weeds have colonial behavior and were introduced by Mehrabian and Lucas in 2006. Invasive weeds are a serious threat to cultivated plants because of their adaptability and are a threat to the overall planting process. The behavior of these weeds has been studied and applied in the invasive weed algorithm. The algorithm of grey wolves, which is considered as a swarm intelligence algorithm, has been used to reach the goal and reach the best solution. The algorithm was designed by SeyedaliMirijalili in 2014 and taking advantage of the intelligence of the squadrons is to avoid falling into local solutions so the new hybridization process between the previous algorithms GWO and IWO and we will symbolize the new algorithm IWOGWO.Comparing the suggested hybrid algorithm with the original algorithms it results were excellent. The optimum solution was found in most of test functions.
机译:在本研究中,首先是两个算法,被认为是混合算法之一。并且它是算法代表了侵入性杂草优化。该算法是一种随机数值算法和表示灰狼优化的第二算法。该算法是智能优化中群体智能的算法之一。侵入性杂草优化的算法受到自然的启发,因为杂草的殖民行为并于2006年被Mehrabian和Lucas介绍。由于适应性,对培养植物的侵袭性杂草是一种严重的威胁,并且对整个种植过程构成威胁。这些杂草的行为已经研究和应用于侵入性杂草算法。被认为是群体智能算法的灰狼算法已被用于达到目标并达到最佳解决方案。该算法于2014年由Seyedalimirijaliil设计,利用中队的智能是为了避免陷入本地解决方案,因此先前算法GWO和IWO之间的新杂交过程,并我们将象征新的算法IWogwo.com Patering提出的混合算法通过原始算法,它的结果非常出色。在大多数测试功能中发现了最佳溶液。

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