Abstract
An effective non-revisiting artificial bee colony (NrABC) algorithm based on the paradigm of artificial bee colony (ABC) is developed in this paper. NrABC is applied to tackle the synthesis of phased linear arrays. Pros and cons of NrABC is provided along with a comparison to standard ABC. Binary space partitioning tree structure is used to record history evolutionary information. Non-revisiting scheme assures NrABC keeping good diversity of population. Moreover, scout bee stage is discarded in NrABC which also removes an algorithmic parameter of standard ABC. Three phased array synthesis examples are employed to study the performance of NrABC. It turns out that under the same experimental configuration, NrABC outperforms standard ABC in terms of both solution quality and reliability in repeated runs.
Highlights
In remote sensing systems of radar networks [1, 2], phased arrays play an important role to ensure the quality of services (QoS) under certain communication requirements [3–5]
5 Conclusions The main advantage of phased arrays is its capability to construct nearly arbitrary far-field pattern. This character is attained by well tuning of the amplitude and phase features of aperture
It is realized by phase shifters and attenuators of all radiators
Summary
In remote sensing systems of radar networks [1, 2], phased arrays play an important role to ensure the quality of services (QoS) under certain communication requirements [3–5]. It turns out that evolutionary computing methods present good performance in handling phased array design problems [7, 8]. It is observed that a great number of function evaluations is needed for artificial bee colony algorithm to obtain a satisfactory solution. A non-revisiting scheme is used to keep population diversity substituting for scout bee stage in ABC.
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