Heap-based political optimizer

A new hybrid metaheuristic algorithm called Heap-Based Political Optimizer (HBPO) has been developed by integrating the ideas from Heap-Based Optimizer (HBO) and Political Optimizer (PO). To tackle the challenging optimization problems, the HBPO mimics corporate hierarchies and political systems observed in the actual world. In contrast to the original PO, HBPO uses a heap-based structure to improve position update methods and population representation, which leads to better exploration and exploitation capabilities. The elimination of party leaders, the incorporation of heap-based relationships, and flexible populations represent some of the primary modifications. 23 benchmark functions used to compare HBPO against PO and HBO. The results demonstrate that HBPO performed better on multimodal and composite functions while maintaining similar performance on unimodal functions. These results showed the robustness and reliability of HBPO in handling high-dimensional optimization problems.