A painless gradient-assisted multi-objective memetic mechanism for solving continuous bi-objective optimization problems

Adriana Lara López; Carlos A.Coello Coello; Oliver Schütze

doi:10.1109/CEC.2010.5586113

A painless gradient-assisted multi-objective memetic mechanism for solving continuous bi-objective optimization problems

Adriana Lara López, Carlos A.Coello Coello, Oliver Schütze

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

13 Scopus citations

Abstract

In this work we present a simple way to introduce gradient-based information as a means to improve the search performed by a multi-objective evolutionary algorithm (MOEA). Our proposal can be easily incorporated into any MOEA, and is able to improve its performance when solving continuous bi-objective problems. We propose a novel mechanism to control the balance between the local search, and the global search performed by a MOEA. We discuss the advantages of the proposed method and its possible use when dealing with more objectives. Finally, we provide some guidelines regarding the use of our proposed approach.

Original language	English
Title of host publication	2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
DOIs	https://doi.org/10.1109/CEC.2010.5586113
State	Published - 2010
Externally published	Yes
Event	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 - Barcelona, Spain Duration: 18 Jul 2010 → 23 Jul 2010

Publication series

Name	2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

Conference

Conference	2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010
Country/Territory	Spain
City	Barcelona
Period	18/07/10 → 23/07/10

Access to Document

10.1109/CEC.2010.5586113

Cite this

López, A. L., Coello, C. A. C., & Schütze, O. (2010). A painless gradient-assisted multi-objective memetic mechanism for solving continuous bi-objective optimization problems. In 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 Article 5586113 (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010). https://doi.org/10.1109/CEC.2010.5586113

López, Adriana Lara ; Coello, Carlos A.Coello ; Schütze, Oliver. / A painless gradient-assisted multi-objective memetic mechanism for solving continuous bi-objective optimization problems. 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010).

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title = "A painless gradient-assisted multi-objective memetic mechanism for solving continuous bi-objective optimization problems",

abstract = "In this work we present a simple way to introduce gradient-based information as a means to improve the search performed by a multi-objective evolutionary algorithm (MOEA). Our proposal can be easily incorporated into any MOEA, and is able to improve its performance when solving continuous bi-objective problems. We propose a novel mechanism to control the balance between the local search, and the global search performed by a MOEA. We discuss the advantages of the proposed method and its possible use when dealing with more objectives. Finally, we provide some guidelines regarding the use of our proposed approach.",

author = "L{\'o}pez, {Adriana Lara} and Coello, {Carlos A.Coello} and Oliver Sch{\"u}tze",

year = "2010",

doi = "10.1109/CEC.2010.5586113",

language = "Ingl{\'e}s",

isbn = "9781424469109",

series = "2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010",

booktitle = "2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010",

note = "2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 ; Conference date: 18-07-2010 Through 23-07-2010",

}

López, AL, Coello, CAC & Schütze, O 2010, A painless gradient-assisted multi-objective memetic mechanism for solving continuous bi-objective optimization problems. in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010., 5586113, 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010, Barcelona, Spain, 18/07/10. https://doi.org/10.1109/CEC.2010.5586113

A painless gradient-assisted multi-objective memetic mechanism for solving continuous bi-objective optimization problems. / López, Adriana Lara; Coello, Carlos A.Coello; Schütze, Oliver.
2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. 5586113 (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - In this work we present a simple way to introduce gradient-based information as a means to improve the search performed by a multi-objective evolutionary algorithm (MOEA). Our proposal can be easily incorporated into any MOEA, and is able to improve its performance when solving continuous bi-objective problems. We propose a novel mechanism to control the balance between the local search, and the global search performed by a MOEA. We discuss the advantages of the proposed method and its possible use when dealing with more objectives. Finally, we provide some guidelines regarding the use of our proposed approach.

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DO - 10.1109/CEC.2010.5586113

M3 - Contribución a la conferencia

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T3 - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

BT - 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

T2 - 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010

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López AL, Coello CAC, Schütze O. A painless gradient-assisted multi-objective memetic mechanism for solving continuous bi-objective optimization problems. In 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. 5586113. (2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010). doi: 10.1109/CEC.2010.5586113

A painless gradient-assisted multi-objective memetic mechanism for solving continuous bi-objective optimization problems

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