A New Lagrangian Problem Crossover: A Systematic Review and Meta-Analysis of Crossover Standards
April 21, 2022 ยท Declared Dead ยท + Add venue
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Authors
Aso M. Aladdin, Tarik A. Rashid
arXiv ID
2204.10890
Category
cs.NE: Neural & Evolutionary
Cross-listed
cs.AI
Citations
0
Last Checked
4 months ago
Abstract
The performance of most evolutionary metaheuristic algorithms relays on various operatives. One of them is the crossover operator, which is divided into two types: application dependent and application independent crossover operators. These standards always help to choose the best-fitted point in the evolutionary algorithm process. High efficiency of crossover operators allows engineers to minimize errors in engineering application optimization while saving time and avoiding costly. There are two crucial objectives behind this paper; at first, it is an overview of crossover standards classification that has been used by researchers for solving engineering operations and problem representation. The second objective of this paper; The significance of novel standard crossover is proposed depending on Lagrangian Dual Function (LDF) to progress the formulation of the Lagrangian Problem Crossover (LPX) as a new standard of systematic operator. The proposed crossover standards result for 100 generations of parent chromosomes are compared to the BX and SBX standards, which are the communal real-coded crossover standards. The accuracy and performance of the proposed standard have evaluated by three unimodal test functions. Besides, the proposed standard results are statistically demonstrated and proved that it has an excessive ability to generate and enhance the novel optimization algorithm compared to BX and SBX
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