Zorica Stanimirović

TL;DR: Two genetic algorithm approaches are proposed for solving the Uncapacitated Single Allocation p-Hub Median Problem (USApHMP) and one approach achieves all previously known optimal solutions and achieves the best-known solutions on large-scale instances.

TL;DR: A heuristic method, based on a genetic algorithm (GA) approach, is proposed for solving the Capacitated Single Allocation p-Hub Median Problem, which uses binary encoding and modified genetic operators.

TL;DR: The results of computational experiments show that the proposed algorithm outperformed genetic algorithms and grid search considering accuracy of classification and it was compared to other approaches from literature.

TL;DR: Two new heuristic approaches to solve the Discrete Ordered Median Problem (DOMP) are presented, named HGA1 and HGA2, based on a hybrid of genetic algorithms and a generalization of the well-known Fast Interchange heuristic.

TL;DR: This paper proposes two evolutionary algorithms (EAs) that use binary encoding and standard genetic operators adapted to the capacitated hub location problem that obtains high-quality solutions for larger problem dimensions and provides solutions for large-scale instances that have not been addressed in the literature so far.