Effective anytime algorithm for multiobjective combinatorial optimization problems
<|reference_start|>Effective anytime algorithm for multiobjective combinatorial optimization problems: 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.<|reference_end|>
@article{domínguez-ríos2024effective,
    title={Effective anytime algorithm for multiobjective combinatorial
  optimization problems},
    author={Miguel 'Angel Dom'inguez-R'ios, Francisco Chicano, Enrique Alba},
    journal={Inf. Sci. 565: 210-228 (2021)},
    year={2024},
    doi={10.1016/j.ins.2021.02.074},
    archivePrefix={arXiv},
    eprint={2403.08807},
    primaryClass={cs.NE cs.AI}
}