Evolutionary mating algorithm

Mohd Herwan, Sulaiman and Zuriani, Mustaffa and Mohd Mawardi, Saari and Hamdan, Daniyal and Mirjalili, Seyedali (2023) Evolutionary mating algorithm. Neural Computing and Applications, 35 (1). pp. 487-516. ISSN 0941-0643. (Published)

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This paper proposes a new evolutionary algorithm namely Evolutionary Mating Algorithm (EMA) to solve constrained optimization problems. The algorithm is based on the adoption of random mating concept from Hardy–Weinberg equilibrium and crossover index in order to produce new offspring. In this algorithm, effect of the environmental factor (i.e. the presence of predator) has also been considered and treated as an exploratory mechanism. The EMA is initially tested on the 23 benchmark functions to analyze its effectiveness in finding optimal solutions for different search spaces. It is then applied to Optimal Power Flow (OPF) problems with the incorporation of Flexible AC Transmission Systems (FACTS) devices and stochastic wind power generation. The extensive comparative studies with other algorithms demonstrate that EMA provides better results and can be used in solving real optimization problems from various fields.

Item Type: Article
Additional Information: Indexed by Scopus
Uncontrolled Keywords: Evolutionary mating algorithm; FACTS devices; Optimal power flow; Optimization techniques
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
T Technology > T Technology (General)
T Technology > TA Engineering (General). Civil engineering (General)
T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: College of Engineering
Faculty of Computing
Faculty of Electrical and Electronic Engineering Technology
Depositing User: Mr Muhamad Firdaus Janih@Jaini
Date Deposited: 31 Oct 2023 06:56
Last Modified: 31 Oct 2023 06:56
URI: http://umpir.ump.edu.my/id/eprint/38695
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