### Skapa referens, olika format (klipp och klistra)

**Harvard**

Karlsson, K. och Lans, T. (2013) *Big data algorithm optimization*. Göteborg : Chalmers University of Technology

** BibTeX **

@mastersthesis{

Karlsson2013,

author={Karlsson, Kasper and Lans, Tobias},

title={Big data algorithm optimization},

abstract={When sales representatives and customers negotiate, it must be confirmed that the final
deals will render a high enough profit for the selling company. Large companies have
different methods of doing this, one of which is to run sales simulations. Such simulation
systems often need to perform complex calculations over large amounts of data, which
in turn requires efficient models and algorithms.
This project intends to evaluate whether it is possible to optimize and extend an
existing sales system called PCT, which is currently suffering from unacceptably high
running times in its simulation process. This is done through analysis of the current
implementation, followed by optimization of its models and development of efficient
algorithms. The performance of these optimized and extended models are compared to
the existing one in order to evaluate their improvement.
The conclusion of this project is that the simulation process in PCT can indeed
be optimized and extended. The optimized models serve as a proof of concept, which
shows that results identical to the original system's can be calculated within < 1% of
the original running time for the largest customers.},

publisher={Institutionen för data- och informationsteknik (Chalmers), Chalmers tekniska högskola},

place={Göteborg},

year={2013},

note={71},

}

** RefWorks **

RT Generic

SR Electronic

ID 184652

A1 Karlsson, Kasper

A1 Lans, Tobias

T1 Big data algorithm optimization

YR 2013

AB When sales representatives and customers negotiate, it must be confirmed that the final
deals will render a high enough profit for the selling company. Large companies have
different methods of doing this, one of which is to run sales simulations. Such simulation
systems often need to perform complex calculations over large amounts of data, which
in turn requires efficient models and algorithms.
This project intends to evaluate whether it is possible to optimize and extend an
existing sales system called PCT, which is currently suffering from unacceptably high
running times in its simulation process. This is done through analysis of the current
implementation, followed by optimization of its models and development of efficient
algorithms. The performance of these optimized and extended models are compared to
the existing one in order to evaluate their improvement.
The conclusion of this project is that the simulation process in PCT can indeed
be optimized and extended. The optimized models serve as a proof of concept, which
shows that results identical to the original system's can be calculated within < 1% of
the original running time for the largest customers.

PB Institutionen för data- och informationsteknik (Chalmers), Chalmers tekniska högskola,PB Institutionen för data- och informationsteknik (Chalmers), Chalmers tekniska högskola,

LA eng

LK http://publications.lib.chalmers.se/records/fulltext/184652/184652.pdf

OL 30