Three Approaches to Solve Combinatorial Optimization Problems using Simulated Kalman Filter

Zulkifli, Md. Yusof and Ismail, Ibrahim and Zuwairie, Ibrahim and Khairul Hamimah, Abas and Shahdan, Sudin and Nor Azlina, Ab. Aziz and Nor Hidayati, Abd Aziz and Mohd Saberi, Mohamad (2016) Three Approaches to Solve Combinatorial Optimization Problems using Simulated Kalman Filter. In: Proceedings of The National Conference for Postgraduate Research (NCON-PGR 2016) , 24-25 September 2016 , Universiti Malaysia Pahang (UMP), Pekan, Pahang. pp. 951-960..

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Inspired by the estimation capability of Kalman filter, we have recently introduced 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, three extended versions of SKF algorithm, which is termed as Angle Modulated SKF (AMSKF), Distance Evaluated SKF (DESKF), and Binary SKF (BSKF), are proposed. A set of traveling salesman problems is used to evaluate the performance of the proposed algorithms.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: simulated kalman filter; traveling salesman problem; combinatorial optimization
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Noorul Farina Arifin
Date Deposited: 28 Nov 2016 03:13
Last Modified: 08 Feb 2018 03:07
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