A new bio-inspired optimization algorithm called artificial hummingbird algorithm (AHA) is proposed in this work to solve optimization problems. The AHA algorithm simulates the special flight skills and intelligent foraging strategies of hummingbirds in nature. Three kinds of flight skills utilized in foraging strategies, including axial, diagonal, and omnidirectional flights, are modeled. In addition, guided foraging, territorial foraging, and migrating foraging are implemented, and a visit table is constructed to model the memory function of hummingbirds for food sources. AHA is validated using two sets of numerical test functions, and the results are compared with those obtained from various algorithms. The comparisons demonstrate that AHA is more competitive than other meta-heuristic algorithms and determine high-quality solutions with fewer control parameters. Additionally, the performance of AHA is validated on ten challenging engineering design cases studies. The results show the superior effectiveness of AHA in terms of computational burden and solution precision compared with the existing optimization techniques in literature. The study also explores the application of AHA in hydropower operation design to further demonstrate its potential in practice. The source code of AHA is publicly available at https://seyedalimirjalili.com/aha and https://www.mathworks.com/matlabcentral/fileexchange/101133-artificial-hummingbird-algorithm?s_tid=srchtitle.

在这项工作中提出了一种新的仿生优化算法，称为人工蜂鸟算法（AHA）来解决优化问题。AHA算法模拟自然界中蜂鸟的特殊飞行技能和智能觅食策略。对觅食策略中使用的三种飞行技能进行了建模，包括轴向飞行、对角飞行和全向飞行。此外，还实施了引导觅食、领土觅食和迁徙觅食，并构建了访问表来模拟蜂鸟对食物来源的记忆功能。AHA 使用两组数值测试函数进行验证，并将结果与​​从各种算法获得的结果进行比较。比较表明，AHA 比其他元启发式算法更具竞争力，并且可以用更少的控制参数确定高质量的解决方案。此外，AHA 的性能在十个具有挑战性的工程设计案例研究中得到了验证。结果表明，与文献中现有的优化技术相比，AHA 在计算负担和求解精度方面具有优越的有效性。该研究还探讨了 AHA 在水电运行设计中的应用，以进一步展示其在实践中的潜力。AHA 的源代码可在 https://seyedalimirjalili.com/aha 和 https://www.mathworks.com/matlabcentral/fileexchange/101133-artificial-hummingbird-algorithm?s_tid=srchtitle 上公开获得。AHA 的性能在十个具有挑战性的工程设计案例研究中得到了验证。结果表明，与文献中现有的优化技术相比，AHA 在计算负担和求解精度方面具有优越的有效性。该研究还探讨了 AHA 在水电运行设计中的应用，以进一步展示其在实践中的潜力。AHA 的源代码可在 https://seyedalimirjalili.com/aha 和 https://www.mathworks.com/matlabcentral/fileexchange/101133-artificial-hummingbird-algorithm?s_tid=srchtitle 上公开获得。AHA 的性能在十个具有挑战性的工程设计案例研究中得到了验证。结果表明，与文献中现有的优化技术相比，AHA 在计算负担和求解精度方面具有优越的有效性。该研究还探讨了 AHA 在水电运行设计中的应用，以进一步展示其在实践中的潜力。AHA 的源代码可在 https://seyedalimirjalili.com/aha 和 https://www.mathworks.com/matlabcentral/fileexchange/101133-artificial-hummingbird-algorithm?s_tid=srchtitle 上公开获得。该研究还探讨了 AHA 在水电运行设计中的应用，以进一步展示其在实践中的潜力。AHA 的源代码可在 https://seyedalimirjalili.com/aha 和 https://www.mathworks.com/matlabcentral/fileexchange/101133-artificial-hummingbird-algorithm?s_tid=srchtitle 上公开获得。该研究还探讨了 AHA 在水电运行设计中的应用，以进一步展示其在实践中的潜力。AHA 的源代码可在 https://seyedalimirjalili.com/aha 和 https://www.mathworks.com/matlabcentral/fileexchange/101133-artificial-hummingbird-algorithm?s_tid=srchtitle 上公开获得。