Modified cuckoo search algorithm in weighted sum optimization for linear antenna array synthesis

Abstract

In this study, we proposed a bio-inspired technique known as modified cuckoo search (MCS)-based weighted sum algorithm towards synthesizing symmetric linear array geometry with minimum side lobe level (SLL) and/or nulls control. The newly evolved metaheuristic algorithm was primarily based on the natural obligate brood parasitic behavior of some cuckoo species in combination with the Lévy flight behavior of some birds and fruit flies. Through the integration with the Roulette wheel selection operator and the inertia weight controlling the position (solution) exploration, the MCS-based weighted sum approach optimized concurrently the array element excitation locations, amplitudes, and phases within the uniform pattern and Dolph-Chebyshev window, respectively. The optimal solutions obtained were then compared against the conventional (with λ/2 inter-element distance) and other chosen evolutionary algorithms-based arrays.

Hybridization of Strength Pareto Multiobjective Optimization with Modified Cuckoo Search Algorithm for Rectangular Array

“…10e indicates that the MCSPSOSPEA optimizer also had the remarkable predefined null mitigation of −102.6074 dB around at DoA of 124.3318°. Overall, the proposed MCSPSOSPEA algorithm surpassed the MCSPSO counterpart applied in the weighted-sum MO optimization approach 26 for 2 N = 20 linear antenna array, which had the average SLL between 0.047 and 3.826 dB lower than the conventional array, HPBW of 92°−88° = 4°, and maximum null mitigation of −70.661 dB, respectively. Consequently, this shows that Pareto MO optimization yielded better performance indicator than the weighted-sum approach using the same objective functions.…”

“…The Pareto front approach has shown to be promising in solving MO optimization problems by accelerating convergence and maintaining a high degree of diversity selected from a set of non-dominated solutions. This study primarily extends the research related to the MO optimization via weighted-sum approach for symmetric linear antenna synthesis 26 by deploying the strength Pareto trade-offs of three objective functions, f 1 , f 2 , and f 3 . Precisely, the robustness of hybridization of MCS and PSO known as MCSPSO algorithm is found to have a superior performance than the original CS algorithm after undergoing the weighted-sum MO optimization approach 26 in terms of side lobes suppression, null mitigation, and half-power beamwidth (HPBW) reduction.…”

“…This study primarily extends the research related to the MO optimization via weighted-sum approach for symmetric linear antenna synthesis 26 by deploying the strength Pareto trade-offs of three objective functions, f 1 , f 2 , and f 3 . Precisely, the robustness of hybridization of MCS and PSO known as MCSPSO algorithm is found to have a superior performance than the original CS algorithm after undergoing the weighted-sum MO optimization approach 26 in terms of side lobes suppression, null mitigation, and half-power beamwidth (HPBW) reduction. Alternatively, in this research we put a more concern on the simultaneous trade-off optimization to prevent the possibility of bias among objective functions in weighted sum-approach due to different units or parameters used for each function.…”

Performance analysis of optimized controllers with bio-inspired algorithms

“…This procedure generates a set of random values (with a normal distribution) interacting with each other, which are related to the measured distance between each element of the solution and the elements of the best nest identified, and are added to the current values of each nest. As a result, a set of newly available nests is obtained whose location within the search space has been found based on random values and influenced to some extent by the best nest of the previous generation [21][22][23][24][25][26][27][28][29][30].…”

“…If the new nests show better results, the cuckoo egg originally deposited in the nest is eliminated and the nest is maintained with the new solution [21][22][23][24][25][26][27][28][29][30].…”