Changes between Version 2 and Version 3 of Documentation/Howto/OptimizeExternalApplications

Timestamp:

06/03/10 20:50:45 (14 years ago)

Author:

abeham

Comment:

further structure

Documentation/Howto/OptimizeExternalApplications

@@ -5 +5 @@
 The most important part in any optimization problem is the evaluation function. Without knowing about the quality of a certain solution configuration the algorithm is not able to come close to an optimal solution. In NP hard problems evaluating a solution is usually a rather simple task, whereas finding the best solution is extremely difficult. Of course there can be complex problems which require high computational effort to calculate the quality of a solution, but in many cases the evaluation of a solution is rather straight forward. So, if the problem is not a HeuristicLab plugin we assume that it is available in another kind of executable format, either in an application itself or as part of another framework for example. We thus have a situation where we need inter-process communication (IPC). There are several possibilities of how to do IPC, in the following we will explain the approach we offer in HeuristicLab 3.3.
 
-== Architecture ==
+== Architecture Overview ==
 
 === Technology & Background ===
@@ -29 +29 @@
 In this type the received solutions have to be polled. The service receives solutions in its own thread and puts them into a queue, waiting for the developer to process them. It provides two public methods, one that returns the next solution from the queue and blocks until a solution becomes available and another that sends the quality back to HeuristicLab.
 
-== Application Scenarios ==
+=== Application Scenarios ===
 
 One of the application scenarios that we had in mind when designing this interface is the field of simulation-based optimization. There, a simulation model defines a number of parameters which need to be adjusted such that a measured output of the model improves. This can be inventory sizes in a supply-chain scenario, or similarly buffer sizes in an assembly line, or training the weights in a neural network simulator. There are numerous optimization problems that are implemented as simulation models and one of the main problems is talking to them. Many different frameworks exist with which one can conveniently build, run, and test a simulation model, and most of them already have some support for optimization. However that support often is of proprietary nature and little information is available on how these methods perform. HeuristicLab aims to provide an open source alternative and the means of this interface allows simulation experts to use HeuristicLab in the optimization tasks.
 
 Naturally, there exist several more reasons why a problem cannot be modeled in HeuristicLab, such as language or platform dependency and for these purposes this interface should provide a solution.
+
+== Architecture Details ==
+
+== Tutorial ==