README

The Iterative Placement Algorithm is an algorithm designed for placing the most regular polygon modules inside a given border.

ITPLA

ITPLA firstly generates the maximum number of modules and places them randomly. Then the algorithm starts evolving the placement. After reaching some kinds of stable states, a decision will be made whether continue evolving with removing some modules or stop and return the result.

1. Usage

The Iterative Placement Algorithm has two different realization versions:

1. C++

   This version is the alogrithm's prototype. It is based on the C++ language. To realize the GUI, It introduces the Qt library. It also uses CGAL library to do 2d geometric caculation and Box2D library to simulate the movement.

   Because the major purpose is to validate the algorithm, this version has many disadvantages:

   • the runtime enviroment is not easy to setup
   • the type definitions and variable names are confusable
   • it's difficult to add new features for the poor modular design
   • the minimum distance calculation between two objects is complex and just an approximation

2. Python

   For the main task of the algorithm is 2d calculation, physical simulation and GUI, Python maybe a better choice than C++ for

   1. less caring about underlying data types
   2. more powerful and free features help to reduce codes
   3. easily used package manager pip and libraries numpy, box2d and pygame

   This version's goal is for simplifying and enhancing, and the work is still undergoing. The finished part has already shown some advantages:

   • now the enviroment setup is clear and easy
   • the variables are less and their names are meaningful
   • many simple functions are defined and used to simplify and clear the code
   • the general minimum distance calculation procedure is modular and accurate now
   • the lines of code significiantly reduce from 1000+ to 200~, the compact code helps debugging and reading

2. Documentation

3. Licensing

For further license information, please contact the authors.

4. Authors contacts

If you want to be informed about algorithm updates and new releases, obtain further information about the provided code, or contribute to its development please write to:

Xuenan Guo - [email protected]

Fulvio Mastrogiovanni - [email protected]