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Penalty method / Constraint / Linear programming / Genetic algorithm / Evolutionary algorithm / Candidate solution / Interior point method / Shape optimization / Nonlinear programming / Mathematical optimization / Numerical analysis / Mathematical analysis


Penalty Functions Alice E. Smith and David W. Coit
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Document Date: 2010-09-08 06:10:09

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City

Bristol / /

Company

Oxford University Press / ORSA Journal / /

Country

United States / United Kingdom / /

Facility

Institute of Physics Publishing Revised January / Industrial Engineering University of Pittsburgh Pittsburgh / Institute of Physics Publishing / University of Michigan Technical Report / /

IndustryTerm

feasible best solution / search progresses / final infeasible solutions / genetic algorithm / search specific / infeasible solutions / feasible solution / dual genetic algorithm / interior solutions / genetic algorithms / final solution / evolutionary algorithm / infeasible best solution / constant penalty to those solutions / search parameter / search history / optimum solution / search time / feasible solutions / segregated genetic algorithm / infeasible solution / /

Organization

Industrial Engineering University of Pittsburgh Pittsburgh / Institute of Physics Publishing / David W. Coit Department / University of Michigan Technical Report / Oxford University / /

Person

David Fogel Zbigniew Michalewicz / Thomas Baeck David Fogel Zbigniew / Thomas Baeck / Alice E. Smith / David W. Coit / /

Position

Fisher / Chief / /

ProgrammingLanguage

L / J / R / C / /

ProvinceOrState

Pennsylvania / /

Technology

segregated genetic algorithm / Genetic Algorithms / 1994 Genetic algorithms / evolutionary algorithm / dual genetic algorithm / 1995 Genetic algorithms / 1989 Genetic Algorithms / Machine Learning / two genetic algorithm / Simulation / genotype / /

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