#5755. Joint Opposite Selection (JOS): A premiere joint of selective leading opposition and dynamic opposite enhanced Harris’ hawks optimization for solving single-objective problems

July 2026publication date
Proposal available till 11-05-2025
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Journal’s subject area:
Engineering (all);
Computer Science Applications;
Artificial Intelligence;
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Abstract:
In this paper, we proposed Joint Opposite Selection (JOS) operator that is a joint of two opposition learning techniques: the Selective Leading Opposition (SLO) and the Dynamic Opposite (DO). SLO uses a linearly decreasing threshold value to determine the close distance dimension of the search agents. DO provides the search agents chances to expand their abilities in the search space. We applied JOS to the Harris Hawks Optimization (HHO), the performance is increased because JOS balances the capability of exploration phase by using SLO and exploitation phase by using DO. The new algorithm, named Harris’ Hawks Optimization-Joint Opposite Selection (HHO-JOS), is also proposed in this research as an enhanced version of HHO to solve single-objective problems. When the hawks deploy JOS, SLO assists the hawks to succeed in exploitation phase by changing their close distance dimension and DO tries to diverse the search space range of the hawks in the exploration phase using a Random Jump Strategy (RJS).
Keywords:
Dynamic Opposite (DO); Harris’ Hawks Optimization (HHO); Joint Opposite Selection (JOS); Nature-Inspired Optimization Algorithm; Selection Leading Opposition (SLO); Selective Opposition (SO)

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