A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and 2-Opt Operator

Suhazri Amrin, Rahmad and Zuwairie, Ibrahim and Zulkifli, Md. Yusof (2021) A Modified Simulated Kalman Filter Optimizer with State Measurement, Substitution Mutation, Hamming Distance Calculation, and 2-Opt Operator. In: IEEE 19th Student Conference on Research and Development (SCOReD 2021) , 23-25 November 2021 , Kota Kinabalu, Malaysia. pp. 91-95.. ISBN 978-1-6654-0193-7

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Abstract

The simulated Kalman filter (SKF) is an algorithm for population-based optimization based on the Kalman filter framework. Each agent in SKF is treated as a Kalman filter. To find the global optimum, the SKF employs a Kalman filter mechanism that includes prediction, measurement, and estimate. However, the SKF is limited to operating in the numerical search space only. Numerous techniques and modifications have been made to numerical meta-heuristic algorithms in the literature in order to enable them to operate in a discrete search space. This paper presents modifications to measurement and estimation in SKF to accommodate the discrete search space. The modified algorithm is called Discrete Simulated Kalman Filter Optimizer (DSKFO). Additionally, the DSKFO algorithm incorporates the 2-opt operator to improve the solution in solving the travelling salesman problem (TSP). The DSKFO algorithm was compared against four other combinatorial SKF algorithms and outperformed them all.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: Combinatorial, Simulated Kalman Filter, 2-opt, Travelling Salesman Problem
Subjects: T Technology > TS Manufactures
Faculty/Division: Institute of Postgraduate Studies
College of Engineering
Faculty of Mechanical & Manufacturing Engineering
Depositing User: Noorul Farina Arifin
Date Deposited: 07 Feb 2022 02:46
Last Modified: 07 Feb 2022 02:46
URI: http://umpir.ump.edu.my/id/eprint/33311
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