首页> 外文期刊>Latin American Applied Research >A COMPARISON OF METAHEURISTICS ALGORITHMS FOR COMBINATORIAL OPTIMIZATION PROBLEMS. APPLICATION TO PHASE BALANCING IN ELECTRIC DISTRIBUTION SYSTEMS
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A COMPARISON OF METAHEURISTICS ALGORITHMS FOR COMBINATORIAL OPTIMIZATION PROBLEMS. APPLICATION TO PHASE BALANCING IN ELECTRIC DISTRIBUTION SYSTEMS

机译:组合优化问题元算法的比较。在配电系统相平衡中的应用

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摘要

Metaheuristics Algorithms are widely recognized as one of most practical approaches for Combinatorial Optimization Problems. This paper presents a comparison between two metaheuristics to solve a problem of Phase Balancing in Low Voltage Electric Distribution Systems. Among the most representative mono-objective metaheuristics, was selected Simulated Annealing, to compare with a different metaheuristic approach: Evolutionary Particle Swarm Optimization. In this work, both of them are extended to fuzzy domain to modeling a multi-objective optimization, by mean of a fuzzy fitness function. A simulation on a real system is presented, and advantages of Swarm approach are evidenced.
机译:元启发式算法已被广泛认为是解决组合优化问题的最实用方法之一。本文对两种元启发式方法进行了比较,以解决低压配电系统中的相平衡问题。在最具代表性的单目标元启发式方法中,选择了“模拟退火”,以与另一种元启发式方法进行比较:进化粒子群优化。在这项工作中,它们都通过模糊适应度函数扩展到模糊域,以对多目标优化进行建模。提出了在真实系统上的仿真,并证明了Swarm方法的优势。

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