Abstract: In an organization, a group of people working for a common goal may not achieve their goal unless they organize themselves in a hierarchy called Corporate Rank Hierarchy (CRH). This principle motivates us to map the concept of CRH to propose a new algorithm for optimization that logically arranges the search agents in a hierarchy based on their fitness. The proposed algorithm is named as heap-based optimizer (HBO) because it utilizes the heap data structure to map the concept of CRH. The mathematical model of HBO is built on three pillars: the interaction between the subordinates and their immediate boss, the interaction between the colleagues, and self-contribution of the employees. The proposed algorithm is benchmarked with 97 diverse test functions including 29 CEC-BC-2017 functions with very challenging landscapes against 7 highly-cited optimization algorithms including the winner of CEC-BC-2017 (EBO-CMAR). In the first two experiments, the exploitative and explorative behavior of HBO is evaluated by using 24 unimodal and 44 multimodal functions, respectively. It is shown through experiments and Friedman mean rank test that HBO outperforms and secures $1^{st}$ rank. In the third experiment, we use 29 CEC-BC-2017 benchmark functions. According to Friedman mean rank test HBO attains $2^{nd}$ position after EBO-CMAR; however, the difference in ranks of HBO and EBO-CMAR is shown to be statistically insignificant by using Bonferroni method based multiple comparison test. Moreover, it is shown through the Friedman test that the overall rank of HBO is $1^{st}$ for all 97 benchmarks. In the fourth and the last experiment, the applicability on real-world problems is demonstrated by solving 3 constrained mechanical engineering optimization problems. The performance is shown to be superior or equivalent to the other algorithms, which have been used in the literature.
Phases of HBO
- Modeling of Corporate Rank Hierarchy through Heap Data Structure
- Equation for interaction with immediate Boss
- Equation for interaction with a random colleague
- Self-contribution of an employee
Position-updating equations of HBO
HBO Main Framework
Links and downloads:
- Download paper
- HBO Complete Package – MATLAB
- MATLAB implementation of 9 fixed-dimension unimodal benchmarks
- MATLAB implementation of 15 variable-dimension unimodal benchmarks
- MATLAB implementation of 27 fixed-dimension multimodal benchmarks
- MATLAB implementation of 17 variable-dimension multimodal benchmarks
- MATLAB implementation of 29 CEC-BC-2017 benchmarks
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