An Effective Quantum Inspired Genetic Algorithm for Continuous Multiobjective Optimization

Multiobjective Optimization Problems (MOP) can be found in many issues of scientific research, engineering, and in everyday social life. A MOP problem has several objectives that conflict with one another which must be optimized simultaneously. This paper presents a quantum-inspired evolutionary alg...

Full description

Bibliographic Details

Published in:	2019 5th International Conference on Science in Information Technology (ICSITech) pp. 161 - 166
Main Authors:	Abraham, Julisa Bana, Wahyunggoro, Oyas, Setiawan, Noor Akhmad
Format:	Conference Proceeding
Language:	English
Published:	IEEE 01.10.2019
Subjects:	Evolutionary computation Fast Nondominated Sorting Genetic Algorithm Genetic algorithms Information technology Logic gates Measurement Optimization Quantum Inspired Evolutionary Algorithm Sorting Testing
ISBN:	9781728123783, 172812378X
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!