Local Optimum 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...
| Main Authors: | , , , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
Universiti Malaysia Pahang
2016
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/15720/1/P119%20pg892-901.pdf |
| _version_ | 1796991784154300416 |
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| author | Zulkifli, Md. Yusof Ismail, Ibrahim Zuwairie, Ibrahim Khairul Hamimah, Abas Nor Azlina, Ab. Aziz Nor Hidayati, Abd Aziz Mohd Saberi, Mohamad |
| author_facet | Zulkifli, Md. Yusof Ismail, Ibrahim Zuwairie, Ibrahim Khairul Hamimah, Abas Nor Azlina, Ab. Aziz Nor Hidayati, Abd Aziz Mohd Saberi, Mohamad |
| author_sort | Zulkifli, Md. Yusof |
| collection | UMP |
| 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 combinatorial optimization problems, an extended version of SKF algorithm, which is termed as Local Optimum Distance Evaluated Simulated Kalman Filter (LODESKF), is proposed. Similar to existing approach, a mapping function is used to enable the SKF algorithm to operate in binary search space. A set of traveling salesman problems are used to evaluate the performance of the proposed LODESKF against DESKF |
| first_indexed | 2024-03-06T12:10:33Z |
| format | Conference or Workshop Item |
| id | UMPir15720 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:10:33Z |
| publishDate | 2016 |
| publisher | Universiti Malaysia Pahang |
| record_format | dspace |
| spelling | UMPir157202018-02-08T03:02:37Z http://umpir.ump.edu.my/id/eprint/15720/ Local Optimum Distance Evaluated Simulated Kalman Filter For Combinatorial Optimization Problems Zulkifli, Md. Yusof Ismail, Ibrahim Zuwairie, Ibrahim Khairul Hamimah, Abas 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 combinatorial optimization problems, an extended version of SKF algorithm, which is termed as Local Optimum Distance Evaluated Simulated Kalman Filter (LODESKF), is proposed. Similar to existing approach, a mapping function is used to enable the SKF algorithm to operate in binary search space. A set of traveling salesman problems are used to evaluate the performance of the proposed LODESKF against DESKF Universiti Malaysia Pahang 2016 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/15720/1/P119%20pg892-901.pdf Zulkifli, Md. Yusof and Ismail, Ibrahim and Zuwairie, Ibrahim and Khairul Hamimah, Abas and Nor Azlina, Ab. Aziz and Nor Hidayati, Abd Aziz and Mohd Saberi, Mohamad (2016) Local Optimum Distance Evaluated Simulated Kalman Filter For Combinatorial Optimization Problems. In: Proceedings of The National Conference for Postgraduate Research (NCON-PGR 2016) , 24-25 September 2016 , Universiti Malaysia Pahang (UMP), Pekan, Pahang. pp. 892-901.. http://umpir.ump.edu.my/15720/1/P119%20pg892-901.pdf |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Zulkifli, Md. Yusof Ismail, Ibrahim Zuwairie, Ibrahim Khairul Hamimah, Abas Nor Azlina, Ab. Aziz Nor Hidayati, Abd Aziz Mohd Saberi, Mohamad Local Optimum Distance Evaluated Simulated Kalman Filter For Combinatorial Optimization Problems |
| title | Local Optimum Distance Evaluated Simulated Kalman Filter For Combinatorial Optimization Problems |
| title_full | Local Optimum Distance Evaluated Simulated Kalman Filter For Combinatorial Optimization Problems |
| title_fullStr | Local Optimum Distance Evaluated Simulated Kalman Filter For Combinatorial Optimization Problems |
| title_full_unstemmed | Local Optimum Distance Evaluated Simulated Kalman Filter For Combinatorial Optimization Problems |
| title_short | Local Optimum Distance Evaluated Simulated Kalman Filter For Combinatorial Optimization Problems |
| title_sort | local optimum distance evaluated simulated kalman filter for combinatorial optimization problems |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/15720/1/P119%20pg892-901.pdf |
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