Directed intervention crossover applied to bio-control scheduling

Paul M. Godley; David E. Cairns; Julie Cowie

doi:10.1109/CEC.2007.4424531

Directed intervention crossover applied to bio-control scheduling

Paul M. Godley, David E. Cairns, Julie Cowie

NMAHP

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

Abstract

This paper describes two directed intervention crossover approaches that are applied to a bio-control dynamic system. Unlike traditional uniform crossover, both the calculated expanding bin (CalEB) method and targeted intervention with stochastic selection (TInSSel) approach actively choose an intervention level and spread based on the fitness of the parents selected for crossover. Results indicate that these approaches lead to significant improvements over uniform crossover (UC) when a penalty is introduced for each intervention point used by the crossover algorithm.

Original language	English
Title of host publication	2007 IEEE Congress on Evolutionary Computation
Publisher	IEEE
Pages	638-645
Number of pages	8
DOIs	https://doi.org/10.1109/CEC.2007.4424531
Publication status	Published - 30 Nov 2006

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Keywords

bio-control dynamic system;bio-control scheduling;calculated expanding bin;directed intervention crossover;stochastic selection;targeted intervention;uniform crossover;biocontrol;scheduling;stochastic processes;
evolutionary computation
Bio-Control
Scheduling
stochastic processes

Cite this

Godley, P. M., Cairns, D. E., & Cowie, J. (2006). Directed intervention crossover applied to bio-control scheduling. In 2007 IEEE Congress on Evolutionary Computation (pp. 638-645). IEEE. https://doi.org/10.1109/CEC.2007.4424531

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title = "Directed intervention crossover applied to bio-control scheduling",

abstract = "This paper describes two directed intervention crossover approaches that are applied to a bio-control dynamic system. Unlike traditional uniform crossover, both the calculated expanding bin (CalEB) method and targeted intervention with stochastic selection (TInSSel) approach actively choose an intervention level and spread based on the fitness of the parents selected for crossover. Results indicate that these approaches lead to significant improvements over uniform crossover (UC) when a penalty is introduced for each intervention point used by the crossover algorithm.",

keywords = "bio-control dynamic system;bio-control scheduling;calculated expanding bin;directed intervention crossover;stochastic selection;targeted intervention;uniform crossover;biocontrol;scheduling;stochastic processes;, evolutionary computation , Bio-Control, Scheduling, stochastic processes",

author = "Godley, {Paul M.} and Cairns, {David E.} and Julie Cowie",

year = "2006",

month = nov,

day = "30",

doi = "10.1109/CEC.2007.4424531",

language = "English",

pages = "638--645",

booktitle = "2007 IEEE Congress on Evolutionary Computation",

publisher = "IEEE",

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AU - Godley, Paul M.

AU - Cairns, David E.

AU - Cowie, Julie

PY - 2006/11/30

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N2 - This paper describes two directed intervention crossover approaches that are applied to a bio-control dynamic system. Unlike traditional uniform crossover, both the calculated expanding bin (CalEB) method and targeted intervention with stochastic selection (TInSSel) approach actively choose an intervention level and spread based on the fitness of the parents selected for crossover. Results indicate that these approaches lead to significant improvements over uniform crossover (UC) when a penalty is introduced for each intervention point used by the crossover algorithm.

AB - This paper describes two directed intervention crossover approaches that are applied to a bio-control dynamic system. Unlike traditional uniform crossover, both the calculated expanding bin (CalEB) method and targeted intervention with stochastic selection (TInSSel) approach actively choose an intervention level and spread based on the fitness of the parents selected for crossover. Results indicate that these approaches lead to significant improvements over uniform crossover (UC) when a penalty is introduced for each intervention point used by the crossover algorithm.

KW - bio-control dynamic system;bio-control scheduling;calculated expanding bin;directed intervention crossover;stochastic selection;targeted intervention;uniform crossover;biocontrol;scheduling;stochastic processes;

KW - evolutionary computation

KW - Bio-Control

KW - Scheduling

KW - stochastic processes

U2 - 10.1109/CEC.2007.4424531

DO - 10.1109/CEC.2007.4424531

M3 - Conference contribution

SP - 638

EP - 645

BT - 2007 IEEE Congress on Evolutionary Computation

PB - IEEE

ER -

Documents and Links

10.1109/CEC.2007.4424531