Effective anytime algorithm for multiobjective combinatorial optimization problems

• URL: http://arxiv.org/abs/2403.08807v1
• Date: Tue, 6 Feb 2024 11:53:44 GMT
• Title: Effective anytime algorithm for multiobjective combinatorial optimization problems
• Authors: Miguel Ángel Domínguez-Ríos, Francisco Chicano, Enrique Alba,
• Abstract summary: 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. We propose a new exact algorithm for multiobjective optimization combining three novel ideas to enhance the anytime behavior.
• Score: 3.2061579211871383
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: 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.

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