The Whale Optimization Algorithm and Its Implementation in MATLAB
The Whale Optimization Algorithm and Its Implementation in MATLAB
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发表时间：
2018-09
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通讯作者：
S. Adhirai;R. Mahapatra;Paramjit Singh
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作者：
S. Adhirai;R. Mahapatra;Paramjit Singh
摘要-优化是决策和分析物理系统的重要工具。在数学术语中，优化问题是从所有可行解的集合中找到最佳解的问题。本文讨论了鲸鱼优化算法（WOA）及其在不同领域的应用。由于该算法具有独特而强大的功能，因此在MATLAB中进行了测试。WOA算法中使用的基准函数分为：单峰（F1-F7）、多峰（F8-F13）和定维多峰（F14-F23）。在这些基准函数中，我们展示了F7、F11和F19在不同迭代次数下的实验结果。绘制所选函数的搜索空间和目标空间，最后给出WOA找到的目标函数的最优解和最优值。算法结果表明，WOA算法的性能优于当前最先进的元启发式算法和传统算法。
1 Abstract — Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.