Modified multi-verse optimizer for solving numerical optimization problems
The hybrid version of a multi-verse optimizer (MVO) namely the modified multi-verse optimizer (mMVO) is developed in this paper by modifying the position updating equation of MVO. Here two modifications are proposed in the standard MVO. Firstly, an average position selection mechanism is proposed fo...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2020
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/28912/ http://umpir.ump.edu.my/id/eprint/28912/1/10.1109%40I2CACIS49202.2020.9140097.pdf |
| _version_ | 1848823166141464576 |
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| author | Jui, Julakha Jahan Mohd Ashraf, Ahmad Muhammad Ikram, Mohd Rashid |
| author_facet | Jui, Julakha Jahan Mohd Ashraf, Ahmad Muhammad Ikram, Mohd Rashid |
| author_sort | Jui, Julakha Jahan |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | The hybrid version of a multi-verse optimizer (MVO) namely the modified multi-verse optimizer (mMVO) is developed in this paper by modifying the position updating equation of MVO. Here two modifications are proposed in the standard MVO. Firstly, an average position selection mechanism is proposed for solving the local optima problem and secondly, the MVO algorithm is hybrid with another metaheuristics algorithm namely the Sine Cosine Algorithm (SCA) for better balancing the exploration and exploitation of standard MVO algorithm so that it can improve its searching capability. The proposed version of MVO has been evaluated on 23 well known benchmark functions namely unimodal, multimodal and fixed-dimension multimodal benchmark functions and the results are then verified with the standard MVO algorithm. Experimental results demonstrate that the proposed mMVO algorithm gives much better improvement than the standard MVO in the optimization problems in the sense of preventing local optima and increasing the search capability |
| first_indexed | 2025-11-15T02:52:49Z |
| format | Conference or Workshop Item |
| id | ump-28912 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T02:52:49Z |
| publishDate | 2020 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-289122021-03-29T08:49:48Z http://umpir.ump.edu.my/id/eprint/28912/ Modified multi-verse optimizer for solving numerical optimization problems Jui, Julakha Jahan Mohd Ashraf, Ahmad Muhammad Ikram, Mohd Rashid QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) The hybrid version of a multi-verse optimizer (MVO) namely the modified multi-verse optimizer (mMVO) is developed in this paper by modifying the position updating equation of MVO. Here two modifications are proposed in the standard MVO. Firstly, an average position selection mechanism is proposed for solving the local optima problem and secondly, the MVO algorithm is hybrid with another metaheuristics algorithm namely the Sine Cosine Algorithm (SCA) for better balancing the exploration and exploitation of standard MVO algorithm so that it can improve its searching capability. The proposed version of MVO has been evaluated on 23 well known benchmark functions namely unimodal, multimodal and fixed-dimension multimodal benchmark functions and the results are then verified with the standard MVO algorithm. Experimental results demonstrate that the proposed mMVO algorithm gives much better improvement than the standard MVO in the optimization problems in the sense of preventing local optima and increasing the search capability IEEE 2020-06-20 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/28912/1/10.1109%40I2CACIS49202.2020.9140097.pdf Jui, Julakha Jahan and Mohd Ashraf, Ahmad and Muhammad Ikram, Mohd Rashid (2020) Modified multi-verse optimizer for solving numerical optimization problems. In: 2020 IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS) , 20 June 2020 , Shah Alam, Selangor, Malaysia. pp. 81-86.. ISBN 978-1-7281-6133-4 (Published) DOI: 10.1109/I2CACIS49202.2020 DOI: 10.1109/I2CACIS49202.2020.9140097 |
| spellingShingle | QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) Jui, Julakha Jahan Mohd Ashraf, Ahmad Muhammad Ikram, Mohd Rashid Modified multi-verse optimizer for solving numerical optimization problems |
| title | Modified multi-verse optimizer for solving
numerical optimization problems |
| title_full | Modified multi-verse optimizer for solving
numerical optimization problems |
| title_fullStr | Modified multi-verse optimizer for solving
numerical optimization problems |
| title_full_unstemmed | Modified multi-verse optimizer for solving
numerical optimization problems |
| title_short | Modified multi-verse optimizer for solving
numerical optimization problems |
| title_sort | modified multi-verse optimizer for solving
numerical optimization problems |
| topic | QA75 Electronic computers. Computer science QA76 Computer software T Technology (General) |
| url | http://umpir.ump.edu.my/id/eprint/28912/ http://umpir.ump.edu.my/id/eprint/28912/ http://umpir.ump.edu.my/id/eprint/28912/ http://umpir.ump.edu.my/id/eprint/28912/1/10.1109%40I2CACIS49202.2020.9140097.pdf |