Search Results - (( pareto distribution methods algorithm ) OR ( parallel evaluation path algorithm ))
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Quantitative and qualitative analysis of unmanned aerial vehicle's path planning using master-slave parallel vector-evaluated genetic algorithm
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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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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“…Loss of load probability (LLP) and life-cycle cost (LLC) are considered to obtain the Pareto front. The iterative method is employed for validation of the superiority results of the proposed MS-MOSS algorithm. …”
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An evaluation of parallel genetic algorithm for solving shortest path routing problem
Published 2023text::Thesis -
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A memory-guided Jaya algorithm to solve multi-objective optimal power flow integrating renewable energy sources
Published 2025Subjects:Review -
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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. Later, a fuzzy decision technique is applied to extract the trade-off solution set. …”
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Minimizing machining airtime motion with an ant colony algorithm
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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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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…Generalized extreme value (GEV) distribution and generalized Pareto (GP) distribution are two main models in EV theory based on block maxima and threshold exceedances approaches. …”
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A test case generation framework based on UML statechart diagram
Published 2018“…Current studies also hardly address loops and parallel paths issues, and achieved low coverage criteria. …”
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Review on bio-inspired algorithms approach to solve assembly line balancing problem
Published 2019“…Assembly line balancing problem is very crucial to solve since it involves minimizing the time of the machines and operators that required optimal task distribution. The outcome of this paper shows the effectiveness of bio-inspired algorithms in solving assembly line balancing problem compared to traditional method.…”
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Optimal power flow based on fuzzy linear programming and modified Jaya algorithms
Published 2017“…In addition, two novel Jaya-based methods namely, the modified Jaya (MJaya) algorithm and quasi-oppositional modified Jaya (QOMJaya) algorithm are proposed to solve different MOOPF problems. …”
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Bi-objective mixed integer nonlinear programming model for low carbon location-inventory-routing problem with time windows and customer satisfaction
Published 2024“…The IMNSGA-II produces the Pareto optimal solution set, and an entropy–TOPSIS method is used to generate an objective ranking of the solution set for decision-makers. …”
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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty
Published 2024“…Further more, an improved non-dominated sorting genetic algorithm with an elite strategy II (IMNSGA-II) has been developed to solve the two bi-objective models, surpassing existing literature’s algorithms such as Pareto Envelope-based Selection Algorithm II (PESA-II) and NSGA-II. …”
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