A Constraint Consensus Memetic Algorithm for Solving Constrained Optimization Problems

Faculty	Computer Science	Year:	2013
Type of Publication:	ZU Hosted	Pages:	1447-1464
Authors:	Saber Mohamed Staff Zu Site Abstract In Staff Site
Journal:	Engineering Optimization Taylor & Francis	Volume:

Keywords :	, Constraint Consensus Memetic Algorithm , Solving Constrained
Abstract:	Constraint handling is an important aspect of evolutionary constrained optimization. Currently, the mechanism used for constraint handling with evolutionary algorithms mainly assists the selection process, but not the actual search process.

Author Related Publications

Saber Mohamed, "Training and Testing a Self-Adaptive Multi-Operator Evolutionary Algorithm for Constrained Optimization", ELSEVEIR, 2015 More
Saber Mohamed, "An Improved Self-Adaptive Differential Evolution Algorithm for Optimization Problems", IEEE, 2013 More
Saber Mohamed, "Differential Evolution with Dynamic Parameters Selection for Optimization Problems", IEEE, 2014 More
Saber Mohamed, "A Self-Adaptive Combined Strategies Algorithm for Constrained Optimization using Differential Evolution", ELSEVIER, 2014 More
Saber Mohamed, "Self-adaptive Mix of Particle Swarm Methodologies for Constrained Optimization", ELSEVIER, 2014 More

Mohammed Abdel Basset Metwally Attia, "An On-Chain Analysis-Based Approach to Predict Ethereum Prices", IEEE, 2021 More
mahmoud mohamed ismail ali, "Neutrosophic Multi-Criteria Decision Making for Sustainable Procurement in Food Business", University of New Mexico, 2023 More
Mohammed Abdel Basset Metwally Attia, "FV-Seg-Net: Fully Volumetric Network for Accurate Segmentation of COVID-19 Lesions From Chest CT Scans", IEEE, 2022 More