MOEA/D with NBI-style Tchebycheff approach for portfolio management

Qingfu Zhang; Hui Li; Dietmar Maringer; Edward Tsang

doi:10.1109/CEC.2010.5586185

MOEA/D with NBI-style Tchebycheff approach for portfolio management

Qingfu Zhang, Hui Li, Dietmar Maringer, Edward Tsang

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

101 Citations (Scopus)

Abstract

MOEA/D is a generic multiobjective evolutionary optimization algorithm. MOEA/D needs a approach to decompose a multiobjective optimization problem into a number of single objective optimization problems. The commonly-used weighted sum approach and the Tchebycheff approach may not be able to handle disparately scaled objectives. This paper suggests a new decomposition approach, called NBI-style Tchebycheff approach, for MOEA/D to deal with such objectives. A portfolio management MOP has been used as an example to test the effectiveness of MOEA/D with NBI-style Tchebycheff approach. © 2010 IEEE.

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.2010.5586185
Publication status	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

Conference

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

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10.1109/CEC.2010.5586185

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@inproceedings{ae5cd2da46144a62b371f910c353a486,

title = "MOEA/D with NBI-style Tchebycheff approach for portfolio management",

abstract = "MOEA/D is a generic multiobjective evolutionary optimization algorithm. MOEA/D needs a approach to decompose a multiobjective optimization problem into a number of single objective optimization problems. The commonly-used weighted sum approach and the Tchebycheff approach may not be able to handle disparately scaled objectives. This paper suggests a new decomposition approach, called NBI-style Tchebycheff approach, for MOEA/D to deal with such objectives. A portfolio management MOP has been used as an example to test the effectiveness of MOEA/D with NBI-style Tchebycheff approach. {\textcopyright} 2010 IEEE.",

author = "Qingfu Zhang and Hui Li and Dietmar Maringer and Edward Tsang",

year = "2010",

doi = "10.1109/CEC.2010.5586185",

language = "English",

isbn = "9781424469109",

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",

}

Zhang, Q, Li, H, Maringer, D & Tsang, E 2010, MOEA/D with NBI-style Tchebycheff approach for portfolio management. in 2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010., 5586185, 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.2010.5586185

MOEA/D with NBI-style Tchebycheff approach for portfolio management. / Zhang, Qingfu; Li, Hui; Maringer, Dietmar et al.
2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010. 2010. 5586185.

Research output: Chapters, Conference Papers, Creative and Literary Works › RGC 32 - Refereed conference paper (with host publication) › peer-review

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T1 - MOEA/D with NBI-style Tchebycheff approach for portfolio management

AU - Zhang, Qingfu

AU - Li, Hui

AU - Maringer, Dietmar

AU - Tsang, Edward

PY - 2010

Y1 - 2010

N2 - MOEA/D is a generic multiobjective evolutionary optimization algorithm. MOEA/D needs a approach to decompose a multiobjective optimization problem into a number of single objective optimization problems. The commonly-used weighted sum approach and the Tchebycheff approach may not be able to handle disparately scaled objectives. This paper suggests a new decomposition approach, called NBI-style Tchebycheff approach, for MOEA/D to deal with such objectives. A portfolio management MOP has been used as an example to test the effectiveness of MOEA/D with NBI-style Tchebycheff approach. © 2010 IEEE.

AB - MOEA/D is a generic multiobjective evolutionary optimization algorithm. MOEA/D needs a approach to decompose a multiobjective optimization problem into a number of single objective optimization problems. The commonly-used weighted sum approach and the Tchebycheff approach may not be able to handle disparately scaled objectives. This paper suggests a new decomposition approach, called NBI-style Tchebycheff approach, for MOEA/D to deal with such objectives. A portfolio management MOP has been used as an example to test the effectiveness of MOEA/D with NBI-style Tchebycheff approach. © 2010 IEEE.

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U2 - 10.1109/CEC.2010.5586185

DO - 10.1109/CEC.2010.5586185

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 9781424469109

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

Y2 - 18 July 2010 through 23 July 2010

ER -

MOEA/D with NBI-style Tchebycheff approach for portfolio management

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