Nondominated sorting-based disruption in oppositional gravitational search algorithm for stochastic multiobjective short-term hydrothermal scheduling

This article presents a novel framework of nondominated sorting-based disruption in oppositional gravitational search algorithm (NSDOGSA) for solving an inventive stochastic multiobjective short-term hydrothermal scheduling (SMSHTS) problems. An innovative SMSHTS mathematical formulation is derived...

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Vydáno v:	Soft computing (Berlin, Germany) Ročník 23; číslo 16; s. 7229 - 7248
Hlavní autoři:	Nadakuditi, Gouthamkumar, Balusu, Srinivasarao, Bathina, Venkateswararao, Narasimham, P. V. R. L.
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.08.2019 Springer Nature B.V
Témata:	Artificial Intelligence Computational Intelligence Control Decision making Disruption Electric power Engineering Expected values Genetic algorithms Hydraulics Mathematical analysis Mathematical Logic and Foundations Mechatronics Methodologies and Application Multiple objective analysis Operators (mathematics) Optimization Random variables Robotics Scheduling Search algorithms Search process Sorting algorithms Stochastic models Water transportation Spread indicator Gravitational search algorithm Stochastic multiobjective optimization Stochastic hydrothermal scheduling Disruption operator Fuzzy decision making Multi-cascaded reservoir Opposition-based learning
ISSN:	1432-7643, 1433-7479
On-line přístup:	Získat plný text
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