Quasi-oppositional differential evolution

Shahryar Rahnamayan; Hamid R. Tizhoosh; Magdy M.A. Salama

doi:10.1109/CEC.2007.4424748

Quasi-oppositional differential evolution

Shahryar Rahnamayan, Hamid R. Tizhoosh, Magdy M.A. Salama

Artificial Intelligence and Informatics

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

Abstract

In this paper, an enhanced version of the Opposition-Based Differential Evolution (ODE) is proposed. ODE utilizes opposite numbers in the population initialization and generation jumping to accelerate Differential Evolution (DE). Instead of opposite numbers, in this work, quasi opposite points are used. So, we call the new extension Quasi- Oppositional DE (QODE). The proposed mathematical proof shows that in a black-box optimization problem quasi- opposite points have a higher chance to be closer to the solution than opposite points. A test suite with 15 benchmark functions has been employed to compare performance of DE, ODE, and QODE experimentally. Results confirm that QODE performs better than ODE and DE in overall. Details for the proposed approach and the conducted experiments are provided.

Original language	English (US)
Title of host publication	2007 IEEE Congress on Evolutionary Computation, CEC 2007
Pages	2229-2236
Number of pages	8
DOIs	https://doi.org/10.1109/CEC.2007.4424748
State	Published - 2007
Event	2007 IEEE Congress on Evolutionary Computation, CEC 2007 - , Singapore Duration: Sep 25 2007 → Sep 28 2007

Publication series

Name	2007 IEEE Congress on Evolutionary Computation, CEC 2007

Conference

Conference	2007 IEEE Congress on Evolutionary Computation, CEC 2007
Country/Territory	Singapore
Period	9/25/07 → 9/28/07

ASJC Scopus subject areas

Artificial Intelligence
Software
Theoretical Computer Science

Access to Document

10.1109/CEC.2007.4424748

Cite this

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title = "Quasi-oppositional differential evolution",

abstract = "In this paper, an enhanced version of the Opposition-Based Differential Evolution (ODE) is proposed. ODE utilizes opposite numbers in the population initialization and generation jumping to accelerate Differential Evolution (DE). Instead of opposite numbers, in this work, quasi opposite points are used. So, we call the new extension Quasi- Oppositional DE (QODE). The proposed mathematical proof shows that in a black-box optimization problem quasi- opposite points have a higher chance to be closer to the solution than opposite points. A test suite with 15 benchmark functions has been employed to compare performance of DE, ODE, and QODE experimentally. Results confirm that QODE performs better than ODE and DE in overall. Details for the proposed approach and the conducted experiments are provided.",

author = "Shahryar Rahnamayan and Tizhoosh, {Hamid R.} and Salama, {Magdy M.A.}",

year = "2007",

doi = "10.1109/CEC.2007.4424748",

language = "English (US)",

isbn = "1424413400",

series = "2007 IEEE Congress on Evolutionary Computation, CEC 2007",

pages = "2229--2236",

booktitle = "2007 IEEE Congress on Evolutionary Computation, CEC 2007",

note = "2007 IEEE Congress on Evolutionary Computation, CEC 2007 ; Conference date: 25-09-2007 Through 28-09-2007",

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T1 - Quasi-oppositional differential evolution

AU - Rahnamayan, Shahryar

AU - Tizhoosh, Hamid R.

AU - Salama, Magdy M.A.

PY - 2007

Y1 - 2007

N2 - In this paper, an enhanced version of the Opposition-Based Differential Evolution (ODE) is proposed. ODE utilizes opposite numbers in the population initialization and generation jumping to accelerate Differential Evolution (DE). Instead of opposite numbers, in this work, quasi opposite points are used. So, we call the new extension Quasi- Oppositional DE (QODE). The proposed mathematical proof shows that in a black-box optimization problem quasi- opposite points have a higher chance to be closer to the solution than opposite points. A test suite with 15 benchmark functions has been employed to compare performance of DE, ODE, and QODE experimentally. Results confirm that QODE performs better than ODE and DE in overall. Details for the proposed approach and the conducted experiments are provided.

AB - In this paper, an enhanced version of the Opposition-Based Differential Evolution (ODE) is proposed. ODE utilizes opposite numbers in the population initialization and generation jumping to accelerate Differential Evolution (DE). Instead of opposite numbers, in this work, quasi opposite points are used. So, we call the new extension Quasi- Oppositional DE (QODE). The proposed mathematical proof shows that in a black-box optimization problem quasi- opposite points have a higher chance to be closer to the solution than opposite points. A test suite with 15 benchmark functions has been employed to compare performance of DE, ODE, and QODE experimentally. Results confirm that QODE performs better than ODE and DE in overall. Details for the proposed approach and the conducted experiments are provided.

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DO - 10.1109/CEC.2007.4424748

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SN - 9781424413409

T3 - 2007 IEEE Congress on Evolutionary Computation, CEC 2007

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BT - 2007 IEEE Congress on Evolutionary Computation, CEC 2007

T2 - 2007 IEEE Congress on Evolutionary Computation, CEC 2007

Y2 - 25 September 2007 through 28 September 2007

ER -

Quasi-oppositional differential evolution

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