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Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems

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 agen...

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Main Authors: Zulkifli, Md. Yusof, Zuwairie, Ibrahim, Ismail, Ibrahim, Kamil Zakwan, Mohd Azmi, Nor Azlina, Ab. Aziz, Nor Hidayati, Abd. Aziz, Mohd Saberi, Mohamad
Format: Conference or Workshop Item
Language:English
English
Published: 2015
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/11529/1/Distance%20Evaluated%20Simulated%20Kalman%20Filter%20for%20Combinatorial%20Optimization%20Problems.pdf
http://umpir.ump.edu.my/id/eprint/11529/7/Distance%20Evaluated%20Simulated%20Kalman%20Filter%20for%20Combinatorial%20Optimization%20Problems-abstract.pdf
http://umpir.ump.edu.my/id/eprint/11529/
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spelling my.ump.umpir.115292018-02-08T03:24:44Z http://umpir.ump.edu.my/id/eprint/11529/ Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems Zulkifli, Md. Yusof Zuwairie, Ibrahim Ismail, Ibrahim Kamil Zakwan, Mohd Azmi Nor Azlina, Ab. Aziz Nor Hidayati, Abd. Aziz Mohd Saberi, Mohamad TK Electrical engineering. Electronics Nuclear engineering 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 discrete optimization problems, a new distance evaluated approach is proposed and combined with SKF. The performance of the proposed distance evaluated SKF (DESKF) is compared against two other discrete population-based optimization algorithms, namely, binary particle swarm optimization (BPSO) and binary gravitational search algorithm (BGSA). A set of traveling salesman problems are used to evaluate the performance of the proposed DESKF. Based on the analysis of experimental results, we found that the proposed AMSKF is as competitive as BGSA but the BPSO is superior than the both DESKF and BGSA. 2015 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/11529/1/Distance%20Evaluated%20Simulated%20Kalman%20Filter%20for%20Combinatorial%20Optimization%20Problems.pdf application/pdf en http://umpir.ump.edu.my/id/eprint/11529/7/Distance%20Evaluated%20Simulated%20Kalman%20Filter%20for%20Combinatorial%20Optimization%20Problems-abstract.pdf Zulkifli, Md. Yusof and Zuwairie, Ibrahim and Ismail, Ibrahim and Kamil Zakwan, Mohd Azmi and Nor Azlina, Ab. Aziz and Nor Hidayati, Abd. Aziz and Mohd Saberi, Mohamad (2015) Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems. In: International Conference on Electrical Control and Computer Engineering 2015, 27-28 Oct 2015 , Kuantan, Pahang. . (Unpublished)
institution Universiti Malaysia Pahang
building UMP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang
content_source UMP Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Zulkifli, Md. Yusof
Zuwairie, Ibrahim
Ismail, Ibrahim
Kamil Zakwan, Mohd Azmi
Nor Azlina, Ab. Aziz
Nor Hidayati, Abd. Aziz
Mohd Saberi, Mohamad
Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems
description 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 discrete optimization problems, a new distance evaluated approach is proposed and combined with SKF. The performance of the proposed distance evaluated SKF (DESKF) is compared against two other discrete population-based optimization algorithms, namely, binary particle swarm optimization (BPSO) and binary gravitational search algorithm (BGSA). A set of traveling salesman problems are used to evaluate the performance of the proposed DESKF. Based on the analysis of experimental results, we found that the proposed AMSKF is as competitive as BGSA but the BPSO is superior than the both DESKF and BGSA.
format Conference or Workshop Item
author Zulkifli, Md. Yusof
Zuwairie, Ibrahim
Ismail, Ibrahim
Kamil Zakwan, Mohd Azmi
Nor Azlina, Ab. Aziz
Nor Hidayati, Abd. Aziz
Mohd Saberi, Mohamad
author_facet Zulkifli, Md. Yusof
Zuwairie, Ibrahim
Ismail, Ibrahim
Kamil Zakwan, Mohd Azmi
Nor Azlina, Ab. Aziz
Nor Hidayati, Abd. Aziz
Mohd Saberi, Mohamad
author_sort Zulkifli, Md. Yusof
title Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems
title_short Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems
title_full Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems
title_fullStr Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems
title_full_unstemmed Distance Evaluated Simulated Kalman Filter for Combinatorial Optimization Problems
title_sort distance evaluated simulated kalman filter for combinatorial optimization problems
publishDate 2015
url http://umpir.ump.edu.my/id/eprint/11529/1/Distance%20Evaluated%20Simulated%20Kalman%20Filter%20for%20Combinatorial%20Optimization%20Problems.pdf
http://umpir.ump.edu.my/id/eprint/11529/7/Distance%20Evaluated%20Simulated%20Kalman%20Filter%20for%20Combinatorial%20Optimization%20Problems-abstract.pdf
http://umpir.ump.edu.my/id/eprint/11529/
_version_ 1643666692747821056
score 13.211869

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