Abstract
The use of hybrid algorithms for solving real-world optimization problems has become popular since their solution quality can be made better than the algorithms that form them by combining their desirable features. The newly proposed hybrid method which is called Hybrid Differential, Particle, and Harmony (HDPH) algorithm is different from the other hybrid forms since it uses all features of merged algorithms in order to perform efficiently for a wide variety of problems. In the proposed algorithm the control parameters are randomized which makes its implementation easy and provides a fast response. This paper describes the application of HDPH algorithm to linear antenna array synthesis. The results obtained with the HDPH algorithm are compared with three merged optimization techniques that are used in HDPH. The comparison shows that the performance of the proposed algorithm is comparatively better in both solution quality and robustness. The proposed hybrid algorithm HDPH can be an efficient candidate for real-time optimization problems since it yields reliable performance at all times when it gets executed.
Highlights
In recent years, many metaheuristic algorithms have been proposed to solve problems in various fields [1,2,3,4,5,6,7,8,9,10]
This paper describes the application of HDPH algorithm to linear antenna array synthesis
The optimization algorithms use control parameters to have a balance between exploration and exploitation attributes and the performance of an algorithm mainly depends on selection of control parameters properly
Summary
Many metaheuristic algorithms have been proposed to solve problems in various fields [1,2,3,4,5,6,7,8,9,10]. Some well known and preferred metaheuristic algorithms are Clonal Selection Algorithm (CSA), Differential Evolution (DE) algorithm, Particle Swarm Optimization (PSO) algorithm, Artificial Bee Colony (ABC) algorithm, and Harmony Search (HS) Algorithm These algorithms have different operators for achieving exploration and exploitation attributes to find the global optimum point of a given problem. The benefits of HDPH algorithm on a realworld application, namely, the array antenna synthesis problem, both for solution quality and for robustness are shown. This problem can be thought as a nonlinear multidimensional optimization problem which is very difficult to optimize using traditional methods.
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