In many large-scale and time-consuming problems, the application of metaheuristics becomes essential, since these methods enable achieving very close solutions to the exact one in a much shorter time. In this work, we address the problem of portfolio optimization applied to electricity markets negotiation. As in a market environment, decision-making is carried out in very short times, the application of the metaheuristics is necessary. This work proposes a Hybrid model, combining a simplified exact resolution of the method, as a means to obtain the initial solution for a Particle Swarm Optimization (PSO) approach. Results show that the presented approach is able to obtain better results in the metaheuristic search process.

中文翻译：

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基于粒子群优化的电力市场参与混合方法

在许多大规模且耗时的问题中，元启发法的应用变得至关重要，因为这些方法可以在更短的时间内实现对精确方法的非常接近的解决方案。在这项工作中，我们解决了应用于电力市场谈判的投资组合优化问题。就像在市场环境中一样，决策是在很短的时间内完成的，因此需要运用元启发法。这项工作提出了一种混合模型，结合了该方法的简化精确分辨率，以此作为获得粒子群优化（PSO）方法初始解决方案的手段。结果表明，所提出的方法能够在元启发式搜索过程中获得更好的结果。