Modified multi verse optimizer for solving optimization problems using benchmark functions

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

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Abstract

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.

Item Type: Conference or Workshop Item (Lecture)
Uncontrolled Keywords: Optimization, Multi-Verse Optimizer (MVO), Modified Multi-Verse Optimizer (mMVO), Sine Cosine Algorithm (SCA).
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Institute of Postgraduate Studies
Depositing User: Pn. Hazlinda Abd Rahman
Date Deposited: 29 Dec 2022 03:56
Last Modified: 29 Dec 2022 03:56
URI: http://umpir.ump.edu.my/id/eprint/28997
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