Advancements in Intelligent Systems
Comprehensive Audit and Advisory Services for Trading and Risk Management Enhancing Financial Compliance and Strategy Optimization
Authors: Suchismita Chatterjee
Publishing Date: 17-02-2025
ISBN: 978-81-975670-3-2
Abstract
The Gbest-guided Artificial Bee Colony (GABC) algorithm is a latest swarm intelligencebased approach to solve optimization problem. In GABC, the individuals update their respective positions by drawing inspiration from the global best solution available in the current swarm. The GABC is a popular variant of Artificial Bee Colony (ABC) algorithm and is proved to be an efficient algorithm in terms of convergence speed. But, in this strategy, each individual is simply influenced by the global best solution, which may lead to trap in local optima. Therefore, in this paper, a new search strategy, namely “Fully Informed Learning” is incorporated in the onlooker bee phase of ABC algorithm. The developed algorithm is named as Fully Informed Artificial Bee Colony (FABC) algorithm. To validate the performance of FABC, it is tested on 20 well known benchmark optimization problems of different complexities. The results are compared with GABC and some more recent variants of ABC. The results are very promising and show that the proposed algorithm is a competitive algorithm in the field of swarm intelligence-based algorithms.
Keywords
Optimization, Artificial Bee Colony (ABC), Fully Informed Learning, Fully Informed Artificial Bee Colony
Cite as
Suchismita Chatterjee, "Comprehensive Audit and Advisory Services for Trading and Risk Management Enhancing Financial Compliance and Strategy Optimization", In: Chetan Sharma, Vaishali Maheshwari and Harish Sharma (eds), Advancements in Intelligent Systems, SCRS, India, 2025, pp. 95-108. https://doi.org/10.56155/978-81-975670-3-2-7