A novel metaheuristic based on object-oriented programming concepts for engineering optimization

This paper presents a novel, robust, efficient, and simple optimization algorithm called the Object-Oriented Programming Optimization Algorithm (OOPOA) for tackling constrained and unconstrained optimization problems. The algorithm is inspired by the inheritance concept of Object-Oriented programmin...

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Bibliographic Details
Published in:Alexandria engineering journal Vol. 98; pp. 221 - 248
Main Authors: Hosny, Khalid M., Khalid, Asmaa M., Said, Wael, Elmezain, Mahmoud, Mirjalili, Seyedali
Format: Journal Article
Language:English
Published: Elsevier B.V 01.07.2024
Elsevier
Subjects:
Convergence
Exploration
Inheritance
Metaheuristics
Optimization
Population
Population
Exploration
Metaheuristics
Optimization
Inheritance
Convergence
ISSN:1110-0168
Online Access:Get full text
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Summary:This paper presents a novel, robust, efficient, and simple optimization algorithm called the Object-Oriented Programming Optimization Algorithm (OOPOA) for tackling constrained and unconstrained optimization problems. The algorithm is inspired by the inheritance concept of Object-Oriented programming languages, where the features of a class are classified into three types according to inheritance probability: public, private, and protected. The object-oriented programming inheritance concept is implemented in the algorithm to update the population for the next generations. The proposed algorithm ensures exploitation by selecting the solution with the highest fitness to be inherited in each iteration. It ensures exploration by applying a mutation process that helps explore wide regions in the search space. The performance of this technique is demonstrated by solving 34 different optimization tasks, including 20 standard benchmark problems, ten IEEE Congress of Evolutionary Computation benchmark test functions, and four constrained real-world engineering design problems. [Display omitted]
ISSN:1110-0168
DOI:10.1016/j.aej.2024.04.060