Discrete Optimization Two genetic algorithms for solving the uncapacitated single allocation p-hub median problem

This paper deals with the Uncapacitated Single Allocation p-Hub Median Problem (USApHMP). Two genetic algorithm (GA) approaches are proposed for solving this NP-hard problem. New encoding schemes are implemented with appropriate objective functions. Both approaches keep the feasibility of individuals by using specific representation and modified genetic operators. The numerical experiments were carried out on the standard ORLIB hub data set. Both methods proved to be robust and efficient in solving USApHMP with up to 200 nodes and 20 hubs. The second GA approach achieves all previously known optimal solutions and achieves the best-known solutions on large-scale instances.

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