A Hardware Descriptive Approach to Beetle Antennae Search

Abstract

Beetle antennae search (BAS) is a newly developed meta-heuristic algorithm which is effectively used for optimizing objective functions of complex forms or even unknown forms. The common practice for implementing meta-heuristic algorithms including the BAS largely relies on programming in a high-level language and executing the code on a computer platform. However, the high-level implementation of the BAS algorithm hinders it from being used in an embedding system, where real-time operations are normally required. To address this limitation, we present an approach to implementing the BAS algorithm on a field-programmable gate array (FPGA). Specifically, we program the BAS function in the Verilog hardware description language (HDL), which provides a tractable vehicle for implementing the BAS algorithm at the gate level on the FPGA chip. We simulate our Verilog HDL based BAS module with the Modelsim platform. Simulation results validate the feasibility of our proposed Verilog HDL implementation of the BAS. Additionally, we implement the BAS model on the Zynq XC7Z010 platform, with 132.5 µ s latency for model implementation. INDEX TERMS FPGA, beetle antennae search, Verilog HDL, optimization algorithm.

A comprehensive survey of convergence analysis of beetle antennae search algorithm and its applications

“…Additionally, this study extends the application of RTVKP to finance by transforming it into a portfolio insurance problem, with empirical simulations demonstrating its superiority over traditional methodologies. Khan et al applied BAS to solve the intended Markowitz model for portfolio optimization by introducing transaction cost and nonlinear cardinality constraints in the original model (Yue et al 2020). Addressing the non-convex tax-aware portfolio optimization challenge, traditionally approximated as a convex problem, Khan et al introduced the Nonlinear Activated Beetle Antenna Search (NABAS) algorithm (Wang et al 2020b), an innovative nondeterministic meta-heuristic based on BAS.…”

An Improved Beetle Antennae Search Algorithm Based on the Elite Selection Mechanism and the Neighbor Mobility Strategy for Global Optimization Problems

“…Literature [45] introduced a model free approach for online optimization using BAS. Zongcheng Yue et al presented a hardware descriptive approach based BAS [46]. Tamal Ghosh and Kristian Martinsen proposed a collaborative BAS memory based adaptive Learning [47].…”

Diversification of Time-Varying Tangency Portfolio under Nonlinear Constraints through Semi-Integer Beetle Antennae Search Algorithm

“…BAS was chosen in this paper from a vast range of nature inspired meta-heuristics because of its minimal time consumption. BAS has been used to address problems in engineering portfolio optimization [12], asset distribution [13], assets' insurance selection [14], pattern classification [15], machine learning [16], mathematical programming [11], electro-hydraulic position systems [17], integrated circuits [18], tomography diagnosis [19]. This work's main points can be summarized as follows:…”