Posts Tagged ‘ Optimization ’

Changes in optimization performance of gcc over time

September 16, 2012
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Changes in optimization performance of gcc over time

The SPEC benchmarks came out a year after the first release of gcc (in fact gcc was and still is one of the programs included in the benchmark). Compiling the SPEC programs using the gcc option -O2 (sometimes -O3) has always been the way to measure gcc performance, but after 25 years does this way

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Another comparison of heuristic optimizers

August 20, 2012
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Another comparison of heuristic optimizers

A herd of heuristic algorithms is compared using a portfolio optimization. Previously “A comparison of some heuristic optimization methods” used two simple and tiny portfolio optimization problems to compare a number of optimization functions in the R language. This post expands upon that by using a portfolio optimization problem that is of a realistic size … Continue reading...

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Genetic algorithms: a simple R example

August 1, 2012
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Genetic algorithms: a simple R example

Genetic algorithm is a search heuristic. GAs can generate a vast number of possible model solutions and use these to evolve towards an approximation of the best solution of the model. Hereby it mimics evolution in nature. GA generates a population, the individuals in this population (often called chromosomes) have  Read more »

A comparison of some heuristic optimization methods

July 23, 2012
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A comparison of some heuristic optimization methods

A simple portfolio optimization problem is used to look at several R functions that use randomness in various ways to do optimization. Orientation Some optimization problems are really hard. In these cases sometimes the best approach is to use randomness to get an approximate answer. Once you decide to go down this route, you need … Continue reading...

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Linear programming in R: an lpSolveAPI example

July 14, 2012
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Linear programming in R: an lpSolveAPI example

First of all, a shout out to R-bloggers for adding my feed to their website! Linear programming is a valuable instrument when it comes to decision making. This post shows how R in conjunction with the lpSolveAPI package, can be used to build a linear programming model and to analyse  Read more »

Using discrete-event simulation to simulate hospital processes

July 12, 2012
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Using discrete-event simulation to simulate hospital processes

Discrete-event simulation is a very useful tool when it comes to simulating alternative scenario’s for current of future business operations. Let’s take the following case; Patients of an outpatient diabetes clinic are complaining about long waiting times, this seems to have an adverse effect on patient satisfaction and patient retention.  Read more »

Simple and heuristic optimization

June 29, 2012
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Simple and heuristic optimization

This week, at the Rmetrics conference, there has been an interesting discussion about heuristic optimization. The starting point was simple: in complex optimization problems (here we mean with a lot of local maxima, for instance), we do not ne...

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My first R package: parallel differential evolution

January 23, 2012
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My first R package: parallel differential evolution

Last night I was working on a difficult optimization problems, using the wonderful DEoptim package for R. Unfortunately, the optimization was taking a long time, so I thought I'd speed it up using a foreach loop, which resulted in the fo...

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The top 7 portfolio optimization problems

January 5, 2012
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The top 7 portfolio optimization problems

Stumbling blocks on the trek from theory to practical optimization in fund management. Problem 1: portfolio optimization is too hard If you are using a spreadsheet, then this is indeed a problem. Spreadsheets are dangerous when given a complex task.  Portfolio optimization qualifies as complex in this context (complex in data requirements). If you are … Continue reading...

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Regression via Gradient Descent in R

November 27, 2011
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Regression via Gradient Descent in R

In a previous post I derived the least squares estimators using basic calculus, algebra, and arithmetic, and also showed how the same results can be achieved using the canned functions in SAS and R or via the matrix programming capabilities offered by ...

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