Investigating relevant aspects of MOEAs for protein structures prediction
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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On last decades, Evolutionary Algorithms (EA) have been utilized in many engineer's applications. A raising application in electrical engineer has been in network reconfiguration. It can be performed to restore electricity for out-of-service areas after a fault has been identified and isolated. This paper presents an application of multiobjective EA for energy restoration in large-scale distribution networks. To improve EA performance for energy restoration, two techniques are employed: (1) the use of an efficient data structure that produces only feasible configurations, save RAM memory and running time; (2) a multiobjective method based on subpopulation tables. The proposed methodology provides an efficient alternative for network reconfiguration. Moreover, it can be used in problems which require online solutions.