These are the benchmark problems used in,

F. Pulido, L. Mandow and J.L. Pérez de la Cruz (2014): Multiobjective Shortest Path Problems with Lexicographic Goal-based Preferences. European Journal of Operational Research (online, May 15th, 2014).

The paper is available at,

http://dx.doi.org/10.1016/j.ejor.2014.05.008

You are free to use this problem set for your own research. Please, acknowledge and/or reference the above paper if you use this set in your work.


Experiments description:
========================

Benchmark with bi-dimensional grids of 100 × 100 nodes with a vicinity of four neighbours.
	Initial state is located in the center of the grid (50, 50). 
	A single destination node is placed in the diagonal from the center to the bottom right corner.
	Different solution depths are considered, varying from 10 to 100. There are 5 problems for each solution depth.
	For instance, problems 0 to 4 place the destination node at depth = 10, i.e. search from (50, 50) to (55, 55). 
    For each arc, three integer scalar costs c(i, j) = (c1, c2, c3) were randomly generated in the range [1,10], 
	using an uniform distribution, i.e. leading to uncorrelated objectives.	
	
Files format:
=============	

1st line shows the file name
2nd line shows the dimension of the grid
3rd line shows the number of costs
4th line shows the location of the start node
5th line shows the location of the destination node

In order to describe the matrix and its costs each line has the following information:
a= arc, x-ini, y-ini, x-des, y-des, #(c1, c2, c3).
Thus, a 0 0 1 0 #(4 6 2) means an arc from (0, 0) to (1, 0) with costs #(4, 6, 2).
For each node only the necessary arcs are written, adding one column and adding one row to the source node coordinates.
Nodes are numbered from 0 to 99.


Francisco J. Pulido  ---->  francis@lcc.uma.es	
