Linkage-learning Analysis and Development of Model-based Multiobjective Genetic Algorithms

• Grant number: 11/07792-4
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: July 01, 2011
• End date: December 31, 2014
• Field of knowledge: Physical Sciences and Mathematics - Computer Science
• Principal Investigator: Alexandre Cláudio Botazzo Delbem
• Grantee: Jean Paulo Martins
• Host Institution: Instituto de Ciências Matemáticas e de Computação (ICMC). Universidade de São Paulo (USP). São Carlos , SP, Brazil

Abstract

Model-based Genetic Algorithms (MBGAs) represent a class of GAs which use probabilistic models to enable the development of more effective search operators. Although these algorithms show significant results in single-objective optimization, their adaptation to the multiobjective context, in general, have not shown the same success. In this project we investigate the main difficulties faced by those algorithms when solving multiobjective problems and propose ways to circumvent them.

Scientific publications

(5)

(The scientific publications listed on this page originate from the Web of Science or SciELO databases. Their authors have cited FAPESP grant or fellowship project numbers awarded to Principal Investigators or Fellowship Recipients, whether or not they are among the authors. This information is collected automatically and retrieved directly from those bibliometric databases.)

MARTINS, JEAN P.; FONSECA, CARLOS M.; DELBEM, ALEXANDRE C. B.. On the performance of linkage-tree genetic algorithms for the multidimensional knapsack problem. Neurocomputing, v. 146, n. SI, p. 17-29, DEC 25 2014. (11/07792-4)

MARTINS, JEAN P.; DELBEM, ALEXANDRE C. B.. Pairwise independence and its impact on Estimation of Distribution Algorithms. SWARM AND EVOLUTIONARY COMPUTATION, v. 27, p. 80-96, APR 2016. (11/07792-4)

MARTINS, JEAN P.; DELBEM, ALEXANDRE C. B.. Reproductive bias, linkage learning and diversity preservation in bi-objective evolutionary optimization. SWARM AND EVOLUTIONARY COMPUTATION, v. 48, p. 145-155, AUG 2019. (11/07792-4)

MARTINS, JEAN P.; BRINGEL NETO, CONSTANCIO; CROCOMO, MARCIO K.; VITTORI, KARLA; DELBEM, ALEXANDRE C. B.; IEEE. A Comparison of Linkage-learning-based Genetic Algorithms in Multidimensional knapsack Problems. 2013 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), v. N/A, p. 8-pg., 2013-01-01. (11/07792-4)

MARTINS, JEAN P.; FONSECA, CARLOS M.; DELBEM, ALEXANDRE C. B.. On the performance of linkage-tree genetic algorithms for the multidimensional knapsack problem. Neurocomputing, v. 146, p. 13-pg., 2014-12-25. (11/07792-4)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

MARTINS, Jean Paulo. Analysis of linkage learning in evolutionary optimization. 2015. Doctoral Thesis - Universidade de São Paulo (USP). Instituto de Ciências Matemáticas e de Computação (ICMC/SB) São Carlos.