# Deconstructing the Big Valley Search Space Hypothesis

The dataset contains landscape data for "Deconstructing the Big Valley Search Space Hypothesis", G. Ochoa, N. Veerapen. The 16th European Conference on Evolutionary Computation in Combinatorial Optimisation (EvoCOP 2016), 30 March - 1 April 2016, Porto, Portugal.

The data are organised into four folders, one for each of the four instances analysed in the paper, att532, gr666, rat575 and u574. These instances are available from TSPLIB (http://comopt.ifi.uni-heidelberg.de/software/TSPLIB95/).

## How to interprete the data

The networks for each instance are described by four plain text files with the nodes, edges, edge_history and node_history file name extensions. 

The letter and number pairs in the file names indicate the flags that were used to run the linkern program provide in Concorde (http://www.math.uwaterloo.ca/tsp/concorde.html). The I flag defines the way the initial solution is generated and the value 5 defines a custom option that alternates between a random solution and the quick Boruvka method for each run. This is equivalent to alternating between the existing 0 (random) and 4 (quick Boruvka) options. The K flag defines how a kick is computed and the value 3 represents the random walk method. R defines the number of kicks. r defines the number of runs.

The nodes file contains the list of the nodes in the local optima network and each line corresponds to a unique solution. The file is split into three tab-delimited columns:
ID - an integer ID of the solution in the network
FITNESS - the fitness of the solution
SOLUTION - a comma separated representation of the solution where the cities are indexed according to their order of appearance in the TSPLIB instance starting from 0

The edges file contains the list of directed edges in the local optima network and each line corresponds to a unique edge. The file is split into three tab-delimited columns:
ID_START - the ID of the node starting the edge
ID_END - the ID of the node ending the edge
COUNT - the number of times this edge was observed during the sampling procedure

The edge_history file contains a summary of each iteration of the sampling procedure. The file is split into four tab-delimited columns:
RUN - the number of the run
ITER - the number of the iteration within the run
ID_START - the ID of the node starting the edge (the run)
ID_END - the ID of the node ending the edge (the run)

The node_history file contains a summary of each run in the sampling procedure. The file is split into at least four tab-delimited columns:
ITER - the number of the run
START - the ID of the first node in the run
NB_GLOBALS - the number of unique global optima found during the run
GLOBALS - [this column is empty if NB_GlOBALS = 0] the IDs of the global optima nodes in as many columns as the value of NB_GLOBALS