Distance Evaluated Simulated Kalman Filter with State Encoding for Combinatorial Optimization Problems


Ab Aziz, Nor Azlina and Md Yusof, Zulkifli and Mohd Azmi, Kamil Zakwan and Muhammad, Mohd Saberi and Ibrahim, Zuwairie and Adam, Asrul and Ab Rahman, Tasiransurini and Muhammad, Badaruddin and Abdul Aziz, Nor Hidayati and Shapiai, Mohd Ibrahim and Mokhtar, Norrima (2018) Distance Evaluated Simulated Kalman Filter with State Encoding for Combinatorial Optimization Problems. International Journal of Engineering & Technology, 7 (4.27). pp. 22-29. ISSN 2227-524X

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Simulated Kalman Filter (SKF) is a population-based optimization algorithm which exploits the estimation capability of Kalman filter to search for a solution in a continuous search space. The SKF algorithm only capable to solve numerical optimization problems which involve continuous search space. Some problems, such as routing and scheduling, involve binary or discrete search space. At present, there are three modifications to the original SKF algorithm in solving combinatorial optimization problems. Those modified algorithms are binary SKF (BSKF), angle modulated SKF (AMSKF), and distance evaluated SKF (DESKF). These three combinatorial SKF algorithms use binary encoding to represent the solution to a combinatorial optimization problem. This paper introduces the latest version of distance evaluated SKF which uses state encoding, instead of binary encoding, to represent the solution to a combinatorial problem. The algorithm proposed in this paper is called state-encoded distance evaluated SKF (SEDESKF) algorithm. Since the original SKF algorithm tends to converge prematurely, the distance is handled differently in this study. To control and exploration and exploitation of the SEDESKF algorithm, the distance is normalized. The performance of the SEDESKF algorithm is compared against the existing combinatorial SKF algorithm based on a set of Traveling Salesman Problem (TSP).

Item Type: Article
Uncontrolled Keywords: combinatorial optimization, distance evaluated, simulated Kalman filter, state encoding, travelling salesman problem
Subjects: Q Science > QA Mathematics > QA299.6-433 Analysis
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 18 Nov 2020 16:31
Last Modified: 21 Dec 2022 06:31
URII: http://shdl.mmu.edu.my/id/eprint/7405


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