Craig A. Tovey
- Courses2
- Reviews14
- School: Georgia Institute of Technology
- Campus:
- Department: Industrial Engineering
- Email address: Join to see
- Phone: Join to see
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Location:
North Avenue
Atlanta, GA - 30332 - Dates at Georgia Institute of Technology: April 2015 - December 2019
- Office Hours: Join to see
N/A
Would take again: No
For Credit: Yes
0
0
Awful
I went to his office because I thought he had been unfair on one of my assignments. He threw a fit. He said, "Don't push, I may explode!" He told me that I should not care about grades but I think that he needs serious anger-management help. Better to stay far away from him.
Biography
Georgia Institute of Technology - Industrial Engineering
Professor at Georgia Tech
Logistics & Supply Chain
Craig
Tovey
Greater Atlanta Area
Specialties: Mathematical modeling, discrete optimization, probabilistic analysis, political economy, biologically-inspired design
Experience
ILOG
principal software developer
Team member for release 8.0 of CPLEX.
Georgia Tech
Professor
Research and teaching in optimization, mathematical modeling, biologically inspired design, political economy and voting theory, and probabilistic analysis, with applications to manufacturing, logistics, web-hosting, etc.
Education
Harvard University
A.B. Magna Cum Laude
Applied Mathematics
Stanford University
PhD
operations research
Publications
From honeybees to Internet servers: biomimicry for distributed management of Internet hosting centers
BIOINSPIRATION & BIOMIMETICS/IOP Publishing Ltd
An Internet hosting center hosts services on its server ensemble. The center must allocate servers dynamically amongst services to maximize revenue earned from hosting fees. The finite server ensemble, unpredictable request arrival behavior and server reallocation cost make server allocation optimization difficult. Server allocation closely resembles honeybee forager allocation amongst flower patches to optimize nectar influx. The resemblance inspires a honeybee biomimetic algorithm. This paper describes details of the honeybee self-organizing model in terms of information flow and feedback, analyzes the homology between the two problems and derives the resulting biomimetic algorithm for hosting centers. The algorithm is assessed for effectiveness and adaptiveness by comparative testing against benchmark and conventional algorithms. Computational results indicate that the new algorithm is highly adaptive to widely varying external environments and quite competitive against benchmark assessment algorithms. Other swarm intelligence applications are briefly surveyed, and some general speculations are offered regarding their various degrees of success.
