RT Journal Article
T1 Effective anytime algorithm for multiobjective combinatorial optimization problems
A1 Domínguez-Ríos, Miguel Ángel
A1 Alba-Torres, Enrique
A1 Chicano-García, José-Francisco
K1 Algoritmos
AB In multiobjective optimization, the result of an optimization algorithm is a set of efficient solutions from which the decision maker selects one. It is common that not all the efficient solutions can be computed in a short time and the search algorithm has to be stopped prematurely to analyze the solutions found so far. A set of efficient solutions that are well-spread in the objective space is preferred to provide the decision maker with a great variety of solutions. However, just a few exact algorithms in the literature exist with the ability to provide such a well-spread set of solutions at any moment: we call them anytime algorithms. We propose a new exact anytime algorithm for multiobjective combinatorial optimization combining three novel ideas to enhance the anytime behavior. We compare the proposed algorithm with those in the state-of-the-art for anytime multiobjective combinatorial optimization using a set of 480 instances from different well-known benchmarks and four different performance measures: the overall non-dominated vector generation ratio, the hypervolume, the general spread and the additive epsilon indicator. A comprehensive experimental study reveals that our proposal outperforms the previous algorithms in most of the instances.
PB Elsevier
YR 2021
FD 2021-07
LK https://hdl.handle.net/10630/23501
UL https://hdl.handle.net/10630/23501
LA eng
NO Miguel Ángel Domínguez-Ríos, Francisco Chicano, Enrique Alba, "Effective anytime algorithm for multiobjective combinatorial optimization problems", Information Sciences 565: 210-228 (2021).
NO This research has been partially funded by the Spanish Ministry of Economy and Competitiveness (MINECO) and the European Regional Development Fund (FEDER) under contract TIN2017-88213-R (6city project), the European Research Council under contract H2020-ICT-2019-3 (TAILOR project), the University of Málaga, Consejería de Economía y Conocimiento de la Junta de Andalucía and FEDER under contract UMA18-FEDERJA-003 (PRECOG project), the Ministry of Science, Innovation and Universities and FEDER under contract RTC-2017-6714-5, and the University of Málaga under contract PPIT.UMA.B1.2017/07 (EXHAURO Project).
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 24 ene 2026