Path Length Example

This exercise demonstrates how a problem can be mapped onto the Flask model and solved by running the Flask simulator.  Figure 1 shows a graph with 8 nodes labeled “a” through “h”.  The arcs between the nodes represent a distance.  The problem is to discover the shortest distance between “a” and “g”. Figure 1 - The cities and the distances between them by various roads

There are 3 paths from “a” to “g”:  <a,b,e,f,g>, <a,c,e,f,g>, and <a,d,h,g>.  The latter is the shortest.

To solve this problem in the Flask, an analog of the problem must be constructed using Flask atoms and binding sites such that molecules will be constructed that represent only valid paths through the graph.  An atomic machine is needed to find a molecule representing the best solution.  The atoms can then be simulated and a solution discovered.

Figure 2 shows the types of molecules that represent solutions to the path length problem.  At the end of the run, the Flask will contain free atoms, molecules that represent paths through the graph, and partially formed paths.  Only completed paths are shown in the figure.  A completed run will have some concentration of the three molecules.  In setting up the problem, one must make sure that the simulation begins with an ample supply of atoms of each of the 8 types and that the simulation runs long enough to form all possible paths through the graph. Figure 2 - Complete molecules that represent paths from city a to city g

There are two atomic attributes we can use to assign values analogous to parameters in the problem being solved:  mass and bond length.  Since we need a quantity that’s associated with a path instead of a graph node, bond length is used to store path length information.

In designing the binding sites for the atoms, care must be taken to avoid formation of paths that are not valid such as the one where an “a” node binds to both a “b” node and a “d” node.  Using an nOf binding site with n equal to 1 will satisfy this constraint.  One approach is to use 1-Of binding sites for the “a to b”, “a to c”, “a to d” sites and the “e to b” and “e to c” sites.

Mechanisms are also needed to flag a molecule as complete when it contains all the nodes on a path from “a” to “g” and a way to select a molecule that represents a good solution.  For the former, we create a class of atom labeled “S”.  It has two and binding sites “S” and “E” (for start and end) and a conditional binding site labeled “XX”.  “S” and “E” are electrostatic.  We add an “S” binding site to the “a” atoms and an “EE” binding site to the “g” atoms.  When the “S” atom attaches to an “a” and a “g” atom, it then exposes its “X” binding site.  This site exposes the molecule as being a solution to the path length problem.

The second mechanism needed to select the best solution molecule is provided by the Improved Bond Length Comparator (ImprovedBLC) atomic machine, which is labeled “Comparator” in this example.  Unlike the other atoms, which have multiple copies, there is only one “Comparator” atom.  Its job is to attach to two molecules at a time and compare their path lengths.  The molecule with the shortest path remains attached to the comparator.  The second molecule is released after its “X” binding site is removed.  This prevents the molecule with the less optimal solution from being selected for comparison again.  If two molecules have the same path length, one is detached with its “X” binding site removed. Figure 3 - Atoms for the path length problem

Note that it is possible for partial solutions to form that have an exposed "X" binding site since an an "S" atom could bind to an "a" and a "g" atom before the full path is formed.  Due to the relative concentrations of the atoms, it is unlikely that a partially formed solution will bind to the Comparator.  However, a better solution can be modeled after the second Traveling Salesman Problem using IntraMolecular binding sites.

To set up the problem, the atoms described diagrammatically in Figure 3 must be generated in the Flask in concentrations high enough so that molecules of all the path solutions are formed.  A good starting point is to have all the atoms except the comparator have number 10.  There is only one comparator.  The comparator atom has three booleans that can be set from the FlaskRunner GUI or from program calls:  doMax, print, and dissolve.  The doMax boolean indicates that the comparator is looking for maximum path lengths.  In this problem, we want to find the shortest path, so doMax should be false.  The print parameter indicates that the atomic machine should print to standard output each time it makes a comparison.  Print should be false when running from the GUI.  Finally, dissolve indicates that the molecule that loses the comparison should be prevented from bonding to the comparator again by removing the binding site via which it connects to the comparator.  Dissolve should be true.

When run from FlaskRunner, the View Molecules features displays the molecules created by the simulation run.  Clicking on the comparator atom will cause FlaskRunner to create a dialog window with the minimum path length found.  Figure 4 shows a sample solution using the MoleViewer feature of the FlaskRunner application. Figure 4 - MoleView of one solution