BSKF: Binary Simulated Kalman Filter

Zulkifli, Md. Yusof and Ismail, Ibrahim and Siti Nurzulaikha, Satiman and Zuwairie, Ibrahim and Nor Hidayati, Abd Aziz and Nor Azlina, Ab. Aziz (2015) BSKF: Binary Simulated Kalman Filter. In: International Conference on Artificial Intelligence, Modelling and Simuation, 2-4 December 2015 , Kota Kinabalu, Sabah. pp. 1-5..

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Inspired by the estimation capability of Kalman filter, we have recently introduced a novel estimation-based optimization algorithm called simulated Kalman filter (SKF).Every agent in SKF is regarded as a Kalman filter. Based on the mechanism of Kalman filtering and measurement process,every agent estimates the global minimum/maximum.Measurement, which is required in Kalman filtering, is mathematically modelled and simulated. Agents communicate among them to update and improve the solution during the search process. However, the SKF is only capable to solve continuous numerical optimization problem. In order to solve combinatorial optimization problems, an extended version of SKF algorithm, which is termed as Binary SKF (BSKF), is proposed.Similar to existing approach, a mapping function is used to enable the SKF algorithm to operate in binary search space. A set of traveling salesman problems are used to evaluate the performance of the proposed BSKF against Binary Gravitational Search Algorithm (BGSA) and Binary Particle Swarm Optimization (BPSO).

Item Type: Conference or Workshop Item (Speech)
Uncontrolled Keywords: simulated kalman filter; travelling salesman problem; combinatorial optimization
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Mrs. Neng Sury Sulaiman
Date Deposited: 01 Mar 2016 03:27
Last Modified: 08 Feb 2018 03:19
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