Operational decomposition for large scale multi-objective optimization problems-Reference-Cited by-同舟云学术

Operational decomposition for large scale multi-objective optimization problems

Published:2019-07-13 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the Genetic and Evolutionary Computation Conference Companion
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Author:

Antonio Luis Miguel¹,Coello Carlos A. Coello²,Brambila Silvia González²,González Josué Figueroa²,Tapia Guadalupe Castillo²

Affiliation:

1. CINVESTAV-IPN, Mexico City, Mexico

2. UAM Azcapotzalco, Mexico City, Mexico

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3319619.3322068

Reference8 articles.

1. Kalyanmoy Deb Samir Agrawal Amrit Pratap and T. Meyarivan. 2000. A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II. KanGAL report 200001. Indian Institute of Technology Kanpur India. Kalyanmoy Deb Samir Agrawal Amrit Pratap and T. Meyarivan. 2000. A Fast Elitist Non-Dominated Sorting Genetic Algorithm for Multi-Objective Optimization: NSGA-II. KanGAL report 200001. Indian Institute of Technology Kanpur India.

2. An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints

3. A Study of Multiobjective Metaheuristics When Solving Parameter Scalable Problems

4. A comparative study of the effect of parameter scalability in multi-objective metaheuristics

5. A review of multiobjective test problems and a scalable test problem toolkit

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