Back to Results
First PageMeta Content
Cybernetics / Operations research / Genetic algorithms / Quasi-Newton method / BFGS method / Evolutionary algorithm / Gauss–Newton algorithm / Linear programming / Mutation / Mathematical optimization / Numerical analysis / Applied mathematics


Genetic Optimization Using Derivatives∗ by Jasjeet S. Sekhon† and Walter R. Mebane, Jr.‡
Add to Reading List

Document Date: 2002-07-06 02:24:26

Open Document

File Size: 244,87 KB

Share Result on Facebook

City

Lancaster / /

Country

Netherlands / Canada / /

/

Facility

Cornell University / Harvard University / /

IndustryTerm

random search algorithms / search method / evolutionary algorithm / derivative based algorithm / genetic algorithm / trial solution / trial solutions / boundary solutions / search operators / derivative-based optimization algorithms / /

Organization

U.S. House / Social Sciences and Humanities Research Council of Canada / Harvard University / Cornell University / /

Person

Walter R. Mebane / Jr. / /

/

Position

Associate Professor / Department of Government / endogenous switching tobit regression model / Singer / Assistant Professor / Department of Government / /

Product

Lancaster / /

ProvinceOrState

Georgia / /

TVStation

Wand / /

Technology

derivative based algorithm / genetic algorithm / random search algorithms / Gauss-Newton algorithm / derivative-based optimization algorithms / modified BFGS algorithm / /

URL

HTTP /

SocialTag