jaya（51次）.zip_algorithm_jaya_jayaalgorithm_jaya优化算法

共339个文件

txt：328个

m：5个

xlsx：4个

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algorithm

jaya

智能优化算法

130 浏览量 2022-07-15 21:28:57 上传评论收藏 4.32MB ZIP 举报

**Jaya算法详解** Jaya算法，源自梵文“胜利”的意思，是由Vasudevan在2014年提出的一种新型全局优化算法。它是一种基于群体智能的优化方法，适用于解决多模态、非线性和复杂优化问题。与传统的遗传算法、粒子群优化、蚁群算法等相比，Jaya算法最大的亮点在于其简洁的设计和无需任何参数调整。 **算法原理** Jaya算法的核心思想是通过比较每个个体与全局最优解和局部最优解的距离来更新个体的位置。算法流程如下： 1. **初始化**: 随机生成初始种群，每个个体代表一个可能的解。 2. **计算全局最优解和局部最优解**: 找出当前种群中的最佳解作为全局最优解，同时计算每个个体的局部最优解。 3. **迭代过程**: 对于每个个体，按照以下步骤更新位置： - 选择两个随机个体，分别计算它们与全局最优解和局部最优解的差距。 - 更新个体的新位置，取原始位置与两个随机个体位置之间的线性组合，同时考虑与全局最优解和局部最优解的差距。 4. **判断停止条件**: 如果达到预设的最大迭代次数或满足其他停止条件，算法结束；否则，返回步骤2。 **Jaya算法的优点** 1. **无参数**: Jaya算法无需设置学习率、惯性权重等复杂参数，降低了算法使用的复杂性。 2. **简单高效**: 算法结构简单，计算量相对较小，执行效率高。 3. **全局搜索能力**: 通过比较全局最优和局部最优，能有效探索解决方案空间，避免早熟收敛。 4. **适应性强**: 适用于解决各种类型的优化问题，包括线性和非线性、连续和离散问题。 **应用领域** Jaya算法已广泛应用于工程优化、机器学习、能源管理、经济调度、生物医学等领域。例如，在工程设计中优化结构参数、在机器学习中调整模型参数、在电力系统中进行调度优化等。 **总结** Jaya算法作为一种新兴的智能优化算法，以其独特的无参数设计和优秀的全局搜索性能吸引了研究者的关注。尽管相对年轻，但其在解决复杂优化问题上的表现已经证明了其潜力。在实际应用中，Jaya算法可以灵活地与其他技术结合，如深度学习的超参数调优，以提升整体解决方案的质量。对于那些对参数敏感或需要快速找到全局最优解的问题，Jaya算法不失为一个值得尝试的选择。

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jaya（51次）.zip_algorithm_jaya_jaya algorithm_jaya优化算法_智能优化算法（339个子文件）

cec17_func.cpp 41KB

main.m 2KB

popupdate.m 377B

range.m 216B

fitness.m 142B

drawline.m 115B

cec17_func.mexw64 51KB

M_25_D100.txt 2.39MB

M_21_D100.txt 2.39MB

M_22_D100.txt 2.39MB

M_26_D100.txt 2.39MB

M_29_D100.txt 2.39MB

M_24_D100.txt 2.39MB

M_27_D100.txt 2.39MB

M_23_D100.txt 2.39MB

M_30_D100.txt 2.39MB

M_28_D100.txt 2.39MB

M_29_D50.txt 611KB

M_21_D50.txt 611KB

M_24_D50.txt 611KB

M_28_D50.txt 611KB

M_30_D50.txt 611KB

M_22_D50.txt 611KB

M_26_D50.txt 611KB

M_25_D50.txt 611KB

M_27_D50.txt 611KB

M_23_D50.txt 611KB

M_1_D100.txt 244KB

M_20_D100.txt 244KB

M_17_D100.txt 244KB

M_13_D100.txt 244KB

M_16_D100.txt 244KB

M_15_D100.txt 244KB

M_14_D100.txt 244KB

M_18_D100.txt 244KB

M_7_D100.txt 244KB

M_6_D100.txt 244KB

M_19_D100.txt 244KB

M_9_D100.txt 244KB

M_10_D100.txt 244KB

M_3_D100.txt 244KB

M_4_D100.txt 244KB

M_5_D100.txt 244KB

M_2_D100.txt 244KB

M_8_D100.txt 244KB

M_12_D100.txt 244KB

M_11_D100.txt 244KB

M_27_D30.txt 220KB

M_23_D30.txt 220KB

M_24_D30.txt 220KB

M_26_D30.txt 220KB

M_29_D30.txt 220KB

M_28_D30.txt 220KB

M_30_D30.txt 220KB

M_21_D30.txt 220KB

M_25_D30.txt 220KB

M_22_D30.txt 220KB

M_24_D20.txt 98KB

M_28_D20.txt 98KB

M_25_D20.txt 98KB

M_22_D20.txt 98KB

M_27_D20.txt 98KB

M_21_D20.txt 98KB

M_26_D20.txt 98KB

M_23_D20.txt 98KB

M_18_D50.txt 61KB

M_13_D50.txt 61KB

M_17_D50.txt 61KB

M_4_D50.txt 61KB

M_2_D50.txt 61KB

M_15_D50.txt 61KB

M_19_D50.txt 61KB

M_12_D50.txt 61KB

M_8_D50.txt 61KB

M_10_D50.txt 61KB

M_16_D50.txt 61KB

M_14_D50.txt 61KB

M_3_D50.txt 61KB

M_7_D50.txt 61KB

M_9_D50.txt 61KB

M_5_D50.txt 61KB

M_1_D50.txt 61KB

M_20_D50.txt 61KB

M_6_D50.txt 61KB

M_11_D50.txt 61KB

M_23_D10.txt 25KB

M_21_D10.txt 25KB

M_30_D10.txt 25KB

M_29_D10.txt 25KB

M_24_D10.txt 25KB

M_27_D10.txt 25KB

M_26_D10.txt 25KB

M_22_D10.txt 25KB

M_28_D10.txt 25KB

M_25_D10.txt 25KB

shift_data_25.txt 24KB

shift_data_29.txt 24KB

shift_data_21.txt 24KB

shift_data_30.txt 24KB

shift_data_24.txt 24KB

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