On the importance of isolated infeasible solutions in the many-objective constrained NSGA-III-Reference-Cited by-同舟云学术

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On the importance of isolated infeasible solutions in the many-objective constrained NSGA-III

Published:2021-09 Issue: Volume:227 Page:104335
ISSN:0950-7051
Container-title:Knowledge-Based Systems
language:en
Short-container-title:Knowledge-Based Systems

Author:

Elarbi Maha,Bechikh Slim,Said Lamjed Ben

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference72 articles.

1. Multi-Objective Optimization using Evolutionary Algorithms;Deb,2001

2. Evolutionary Algorithms for Solving Multi-Objective Problems;Coello,2002

3. Multi-objective optimization: Classical and evolutionary approaches;Elarbi,2017

4. A fast and elitist multiobjective genetic algorithm: NSGA-II;Deb;IEEE Trans. Evol. Comput.,2002

5. SPEA2: Improving the strength Pareto evolutionary algorithm;Zitzler,2001

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1. A dual-population Constrained Many-Objective Evolutionary Algorithm based on reference point and angle easing strategy;PeerJ Computer Science;2024-07-22

2. Development of an Energy Planning Model Using Temporal Production Simulation and Enhanced NSGA-III;EAI Endorsed Transactions on Energy Web;2024-04-10

3. Thin-walled deployable composite structures: A review;Progress in Aerospace Sciences;2024-04

4. Compensation and profit allocation for collaborative multicenter vehicle routing problems with time windows;Expert Systems with Applications;2023-12

5. A constrained multiobjective differential evolution algorithm based on the fusion of two rankings;Information Sciences;2023-11

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