Modified multi verse optimizer for solving optimization problems using benchmark functions

The hybrid version of 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 modification is proposed in the standard MVO. Firstly, an average position selection mechanism is proposed for so...

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Main Authors: Jui, Julakha Jahan, Mohd Ashraf, Ahmad, Muhammad Ikram, Mohd Rashid
Format: Conference or Workshop Item
Language:English
Published: IEEE 2020
Subjects:
Online Access:http://umpir.ump.edu.my/id/eprint/28997/
http://umpir.ump.edu.my/id/eprint/28997/1/13.%20Modified%20multi%20verse%20optimizer%20for%20solving%20optimization%20problems%20using%20benchmark%20functions.pdf
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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 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 modification is 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 2025-11-15T02:53:08Z
format Conference or Workshop Item
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institution Universiti Malaysia Pahang
institution_category Local University
language English
last_indexed 2025-11-15T02:53:08Z
publishDate 2020
publisher IEEE
recordtype eprints
repository_type Digital Repository
spelling ump-289972022-12-29T03:56:08Z http://umpir.ump.edu.my/id/eprint/28997/ Modified multi verse optimizer for solving optimization problems using benchmark functions Jui, Julakha Jahan Mohd Ashraf, Ahmad Muhammad Ikram, Mohd Rashid TK Electrical engineering. Electronics Nuclear engineering The hybrid version of 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 modification is 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 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/28997/1/13.%20Modified%20multi%20verse%20optimizer%20for%20solving%20optimization%20problems%20using%20benchmark%20functions.pdf Jui, Julakha Jahan and Mohd Ashraf, Ahmad and Muhammad Ikram, Mohd Rashid (2020) Modified multi verse optimizer for solving optimization problems using benchmark functions. In: IEEE International Conference on Automatic Control and Intelligent Systems (I2CACIS 2020) , 15 July 2020 , Shah Alam, Selangor, Malaysia. pp. 81-86.. ISBN 978-1-7281-6133-4 (Published) https://doi.org/10.1109/I2CACIS49202.2020.9140097
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Jui, Julakha Jahan
Mohd Ashraf, Ahmad
Muhammad Ikram, Mohd Rashid
Modified multi verse optimizer for solving optimization problems using benchmark functions
title Modified multi verse optimizer for solving optimization problems using benchmark functions
title_full Modified multi verse optimizer for solving optimization problems using benchmark functions
title_fullStr Modified multi verse optimizer for solving optimization problems using benchmark functions
title_full_unstemmed Modified multi verse optimizer for solving optimization problems using benchmark functions
title_short Modified multi verse optimizer for solving optimization problems using benchmark functions
title_sort modified multi verse optimizer for solving optimization problems using benchmark functions
topic TK Electrical engineering. Electronics Nuclear engineering
url http://umpir.ump.edu.my/id/eprint/28997/
http://umpir.ump.edu.my/id/eprint/28997/
http://umpir.ump.edu.my/id/eprint/28997/1/13.%20Modified%20multi%20verse%20optimizer%20for%20solving%20optimization%20problems%20using%20benchmark%20functions.pdf