Instance data for 'Revisiting transportation problems under Monge costs with applications to location problems'

This dataset accompanies the manuscript titled "Revisiting transportation problems under Monge costs with applications to location problems", in which Monge cost structures are exploited to develop novel mixed-integer linear programming formulations for the Discrete Ordered Median Problem, a unifying model for classical location objectives such as median, center, and cent-dian. The dataset contains the complete set of benchmark instances (instances.zip) used in the paper's computational study, comprising 810 instance files and 30 cost matrix files, all in JSON format.

Each instance file defines a complete problem configuration, including the number of potential locations n, the number of facilities p to be opened, a reference to a cost matrix representing client-facility allocation costs, and a λ-type identifier with the corresponding λ-vector of length n, which determines the weights in the ordered median objective function. Instance names follow the convention n{n}_p{p}_{lamb_type}_{cost_matrix_index}, uniquely encoding the parameter settings and associated cost matrix. The 30 cost matrix files contain randomly generated n × n matrices and follow the naming scheme costs_n{n}_{cost_matrix_index}. Each cost matrix is used by multiple instances with different combinations of p and λ-types.