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Slice sampler algorithm for generalized pareto distribution
Published 2018“…In this paper, we developed the slice sampler algorithm for the generalized Pareto distribution (GPD) model. …”
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A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…In addition, a novel external elitist repository is developed to conserve discovered non-dominated solutions and to produce true and well-distributed Pareto optimal fronts. …”
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Enhanced Micro Genetic Algorithm-Based Models For Multi-Objective Optimization
Published 2014“…Besides that, the quality of good MOP solutions needs to strike a balance between convergence and diversity against the true Pareto front (i.e. distribution of the ideal Pareto optimal solutions). …”
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Multi-objective spiral dynamic algorithms-based for a better accuracy and diversity
Published 2019“…The produced Pareto front curve is a measure of how good the solution produced by the algorithm is. …”
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Location and sizing of distributed generation photovoltaic (DGPV) via multi-objective pareto algorithm
Published 2023Conference Paper -
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Multiple scenarios multi-objective salp swarm optimization for sizing of standalone photovoltaic system
Published 2020“…The third scenario outperforms other scenarios in terms of coverage and convergence of the distribution of solution to the Pareto front. As a conclusion, The MS-MOSS algorithm is found to be very effective in sizing of SAPV system.…”
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NSGA-III algorithm for optimizing robot collaborative task allocation in the internet of things environment
Published 2024“…A genetic algorithm based on speed invariant and the elite algorithm is proposed to solve the multi-TSP assignment problem. …”
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Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation
Published 2016“…This paper proposes an advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization (Advanced-PFNDMOPSO) method for optimal configuration (placement and sizing) of distributed generation (DG) in the radial distribution system. …”
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Advanced Pareto front non-dominated sorting multi-objective particle swarm optimization for optimal placement and sizing of distributed generation
Published 2016“…This paper proposes an advanced Pareto-front non-dominated sorting multi-objective particle swarm optimization (Advanced-PFNDMOPSO) method for optimal configuration (placement and sizing) of distributed generation (DG) in the radial distribution system. …”
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Optimal placement and sizing of renewable distributed generations and capacitor banks into radial distribution systems
Published 2017“…First a set of non-dominated Pareto-front data are called from the algorithm. …”
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Novel distributed algorithm for coalition formation for enhanced spectrum sensing in cognitive radio networks
Published 2017“…In this paper, we propose a novel algorithm for improving spectrum sensing in cognitive radio networks by forming coalitions among cognitive radio users in a fading channel environment. …”
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Improving Vector Evaluated Particle Swarm Optimisation using Multiple Nondominated Leaders
Published 2014“…However, the obtained solutions did not converge close to the Pareto front and also did not distribute evenly over the Pareto front. …”
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Hybrid flow shop scheduling problem with energy utilization using non-dominated sorting genetic algorithm-III (NSGA-III) optimization
Published 2023“…The model was compared with the most sought algorithm and latest multi-objective algorithms, Strength Pareto Evolutionary Algorithm 2 (SPEA -II), Multi-Objective Algorithm Particle Swarm Optimization (MOPSO), Pareto Envelope-based Selection Algorithm II (PESA-II) and Multi-objective Evolutionary Algorithm based on Decomposition (MOEA/D). …”
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Non-dominated sorting manta ray foraging algorithm with an application to optimize PD control
Published 2022“…MFRO is a recent developed algorithm which was inspired from behavior of a cartilaginous fish called Manta Ray. …”
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Novel distributed algorithm for coalition formation in cognitive radio networks for throughput enhancement using matching theory
Published 2017“…The advantage of stable marriage is that it always converges to a stable matching and is Pareto optimal when the preferences of cognitive radios are strict. …”
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