Tag Archives: optimization

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 a given state. Once the population is generated, the state of these individuals is evaluated and graded on their value. The best individuals are then taken and crossed-over – in order to hopefully generate 'better' offspring – to form the new population. In some cases the best individuals in the population are preserved in order to guarantee 'good individuals' in the new generation (this is called elitism).

The GA site by Marek Obitko has a great tutorial for people with no previous knowledge on the subject.

To explain the example I will use my version of the Knapsack problem.

You are going to spend a month in the wilderness. You’re taking a backpack with you, however, the maximum weight it can carry is 20 kilograms. You have a number of survival items available, each with its own number of “survival points”. You’re objective is to maximize the number of survival points.

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August 1, 2012Permalink 22 Comments

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 its results.

The lpSolveAPI package provides a complete implementation of the lp_solve API.

The example case;

A trading company is looking for a way to maximize profit per transportation of their goods. The company has a train available with 3 wagons. When stocking the wagons they can choose between 4 types of cargo, each with its own specifications. How much of each cargo type should be loaded on which wagon in order to maximize profit?

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July 14, 2012Permalink 11 Comments

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. Today, one doctor runs the outpatient clinic. Hospital management has decided that in order to increase patient retention rates, a nurse will be hired to assist and take over some of the doctor’s tasks. This should result in decreased waiting times and, hopefully, increased patient retention rates.

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July 12, 2012Permalink Leave a comment