Álvarez Lois, Pedro Pablo2024-05-202024-05-202019-09-24https://hdl.handle.net/20.500.14468/14569Recent advances in information and communication technologies have led to the expansion of collaborative work. Complex problems in science, engineering, or business are being solved by teams of people working closely with one another. However, forming teams of experts is a computationally challenging problem that requires powerful solution techniques. A metaheuristic algorithm that incorporates some of the principles of quantum computing into an evolutionary structure is presented. The resulting Quantum Evolutionary Algorithm (QEA) has the ability to produce an adequate balance between intensification and diversification during the search process. Numerical experiments have shown that the QEA is able to significantly improve the quality of the solutions for hard instances of the team formation problem, particularly when compared to a standard genetic algorithm. The successful performance of the algorithm requires careful parameter tuning, as well as a mechanism to effectively share information across the population of candidate solutions.enAtribución-NoComercial-SinDerivadas 4.0 Internacionalinfo:eu-repo/semantics/openAccesstesis de maestría