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A new hybrid optimization technique based on antlion and grasshopper optimization algorithms


This paper proposes a new hybrid algorithm that merges the main features of two well-known metaheuristic algorithms; Grasshopper Optimization Algorithm (GOA) and Antlion Optimization (ALO) algorithm. ALO is strong in exploitation due to the mechanism of antlions in hunting other insects. On the other hand, the social forces in GOA represent the strong capability of exploration all over the search space. So, these features give the chance to combine ALO and GOA in one hybrid algorithm that significantly enhances the performance of both methods. The proposed hybrid algorithm is tested on 32 well-known benchmark test functions, 13 functions of the challenging CEC2015 functions, and two real problems in antenna array synthesis where the elements’ excitation amplitudes and phases are optimized to minimize the maximum sidelobe level and impose nulls at specific angles. Comparisons show that the proposed algorithm outperforms 18 well-known optimization methods, including ALO and GOA, in the majority of these tests, with huge differences in some of them, which prove the stability, robustness, and efficiency of the proposed method over other robust algorithms.

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See Tables

Table 4 Unimodal test functions


Table 5 Multimodal and composite functions


Table 6 Results of unimodal benchmark functions


Table 7 Results of multimodal and composite benchmark functions


Table 8 CEC2015 benchmark test functions

8 and

Table 9 The normalized results of CEC2015 functions


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Amaireh, A.A., Al-Zoubi, A.S. & Dib, N.I. A new hybrid optimization technique based on antlion and grasshopper optimization algorithms. Evol. Intel. (2022).

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  • Optimization
  • Metaheuristics algorithms
  • Evolutionary algorithms
  • Benchmark algorithm
  • Antlion optimization algorithm
  • Grasshopper optimization algorithm