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Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems

Zuwairie, Ibrahim and Zulkifli, Md. Yusof and Asrul, Adam and Kamil Zakwan, Mohd Azmi and Tasiransurini, Ab Rahman and Badaruddin, Muhammad and Nor Azlina, Ab. Aziz and Norrima, Mokhtar and Mohd Ibrahim, Shapiai and Mohd Saberi, Mohamad (2018) Distance evaluated simulated kalman filter with state encoding for combinatorial optimization problems. International Journal of Engineering and Technology(UAE), 7 (4). pp. 22-29. ISSN 2227524X

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Abstract

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 algo-rithms 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 algo-rithm 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 combi-natorial SKF algorithm based on a set of Traveling Salesman Problem (TSP).

Item Type: Article
Additional Information: Index by Scopus
Uncontrolled Keywords: Combinatorial optimization; Distance evaluated; Simulated Kalman Filter; State encoding; Travelling salesman problem
Subjects: T Technology > T Technology (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Faculty of Manufacturing Engineering
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 27 Dec 2018 01:22
Last Modified: 27 Dec 2018 01:22
URI: http://umpir.ump.edu.my/id/eprint/22970
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